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Lead Machine Learning Engineer
New York City, NY – Hybrid (3 days per week onsite)

$200,000 – $220,000 Base Salary+ Bonus + RSU package available

THE COMPANY

We are partnering with a leading consumer technology and financial services organization that operates at global scale and serves hundreds of millions of users. The business leverages advanced data, machine learning, and real-time decisioning systems to deliver highly personalized customer experiences across a broad portfolio of digital products.

This is an exciting opportunity to join a rapidly expanding machine learning engineering team at a pivotal stage of growth. The organization is investing heavily in recommendation systems, real-time personalization, machine learning platforms, and next-generation AI capabilities, offering engineers the opportunity to work with large-scale distributed systems and production-grade ML infrastructure.

RESPONSIBILITIES

• Design, build, and maintain scalable infrastructure supporting machine learning training, deployment, and inference workloads.
• Develop and optimize backend services, microservices, and cloud-native applications that power real-time machine learning systems.
• Own and enhance ML platform capabilities across cloud infrastructure, model serving, monitoring, and operational tooling.
• Partner closely with Data Scientists to productionize machine learning models and support real-time recommendation and personalization use cases.
• Improve CI/CD pipelines, infrastructure-as-code frameworks, observability, reliability, and system scalability.
• Participate in operational ownership, incident response, and support for critical production services.

SKILLS AND EXPERIENCE

Must-Have

• 7+ years of software engineering or machine learning engineering experience.
• Strong backend engineering expertise with experience building distributed systems at scale.
• Proven experience developing Scala-based microservices and production-grade backend applications.
• Deep knowledge of AWS cloud services, including machine learning infrastructure and managed platforms.
• Hands-on experience with Kubernetes, Docker, Terraform, and modern CI/CD practices.
• Strong Python programming skills.
• Track record of owning production systems, reliability, monitoring, and operational excellence.

Nice-to-Have

• Experience with machine learning infrastructure, MLOps, or model-serving platforms.
• Knowledge of recommendation systems, personalization engines, or CTR optimization.
• Experience with Datadog observability and monitoring.
• Background in adtech, fintech, e-commerce, or other high-scale consumer platforms.
• Exposure to real-time machine learning applications and online inference systems.

BENEFITS

• Competitive base salary and annual bonus
• Equity participation through RSUs
• Hybrid working model
• Opportunity to work on cutting-edge AI and machine learning initiatives
• Significant career growth and technical leadership opportunities
• Exposure to large-scale, real-time production systems

HOW TO APPLY

Please register your interest by submitting your CV via the Apply link on this page.

KEY TERMS

Lead Machine Learning Engineer | Machine Learning Engineering | ML Infrastructure | Scala | Python | AWS | SageMaker | Kubernetes | Docker | Terraform | CI/CD | Distributed Systems | Recommendation Systems | Real-Time Systems | MLOps | Backend Engineering | Cloud Infrastructure | Platform Engineering | Datadog | Fintech | Personalization | ML Platform | Software Engineering | Hybrid NYC | Technical Leadership

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Lead Backend Engineer – AI

Location: Fully remote within the United States

Employment Type: Full-time, permanent

Role Overview

We are partnering with a healthcare analytics SaaS company to hire a Lead Backend Engineer – AI. This hands-on technical leader will evolve core backend services while building production-ready AI and machine learning capabilities.

You will work across backend engineering, cloud infrastructure, data science, and applied AI to productionize LLM workflows, RAG systems, prediction and scoring services, model serving, and agentic applications. This role is ideal for an engineer with deep Java expertise and practical Python/ML experience who can make sound architectural and build-versus-buy decisions.

Responsibilities

– Lead the design and development of scalable backend services for the healthcare analytics platform

– Build AI-enabled capabilities including LLM integrations, RAG workflows, predictive and scoring services, model serving, and agentic applications

– Partner with Data Science to move models and proof-of-concepts into reliable production systems

– Develop APIs and services using server-side Java and Python/FastAPI

– Build and maintain ML pipelines, model deployment workflows, and model lifecycle processes

– Use tools such as MLflow for experiment tracking, model management, and deployment

– Design retrieval systems using vector databases, embeddings, and document search

– Evaluate build-versus-buy decisions across AI tooling, model providers, orchestration platforms, and vector stores

Requirements

– 10+ years of software engineering experience, including substantial backend or distributed systems work

– Strong server-side Java development experience

– Production experience with Linux, cloud infrastructure, and scalable service architectures

– Hands-on experience building and operating AI or machine learning systems in production

– Strong Python experience, including FastAPI

– Experience with LLM applications, LangChain or similar orchestration frameworks, and agentic workflows

– Experience with vector databases, embeddings, RAG architectures, and retrieval systems

– Experience with model serving, ML pipelines, model deployment, and lifecycle management

– Familiarity with MLflow or comparable tools for experiment tracking and model registry

Nice to Haves

– Healthcare, healthcare analytics, health tech, or regulated SaaS experience

– Experience with sensitive data, security, privacy, or compliance-focused systems

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Senior AI Product Manager / AI Product Lead

Hybrid | San Francisco, CA (3 days onsite)
Base Salary: Up to $175,000 + RSUs
U.S. Citizens or Green Card Holders only

We’re partnering with a high-growth technology company building next-generation AI-powered products and are seeking a Senior AI Product Manager to drive the strategy, roadmap, and delivery of innovative AI solutions.

What You’ll Do

• Lead the development of customer-facing AI products and features.
• Define product vision, strategy, and roadmap for AI initiatives.
• Partner closely with Engineering, Design, Data Science, and executive stakeholders.
• Translate emerging AI capabilities into scalable, impactful user experiences.
• Drive requirements, prioritization, and execution in a fast-paced environment.

What We’re Looking For

• 5+ years of Product Management experience, including AI/ML-powered products.
• Strong understanding of LLMs, Generative AI, AI agents, RAG, or related technologies.
• Experience launching and scaling enterprise SaaS products.
• Proven ability to work cross-functionally and influence stakeholders.
• Excellent communication and strategic thinking skills.

Why Consider This Opportunity?

• Work on cutting-edge AI products with significant market impact.
• Join a well-funded, rapidly growing organization.
• Competitive compensation package including base salary up to $175K plus RSUs.
• Hybrid work environment in San Francisco.

If you’re interested in learning more about this confidential opportunity, please apply or message me directly for a private discussion.

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#AIJobs #ProductManagement #GenerativeAI #ArtificialIntelligence #SaaS #ProductManager #SanFranciscoJobs #Hiring #TechJobs #MachineLearning #AIProductManager

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Senior Software Engineer (Backend)

Location: Tempe, AZ (Hybrid | 4 days onsite)
Compensation: Up to $140,000 base + bonus
Relocation: Available
Sponsorship: Not available. Candidates requiring current or future sponsorship (H-1B, H-1B Transfer, F-1/OPT, CPT, STEM OPT, H-4 EAD, etc.) cannot be considered.

About the Role

We’re seeking a Senior Software Engineer (Backend) to join a cloud-native development team building APIs and platforms that support mobile applications, customer portals, websites, internal systems, and third-party integration’s.

This is a hands-on role with a strong backend focus (80% backend / 20% frontend) working in an AWS serverless environment.

Responsibilities

• Design, build, and maintain scalable APIs and microservices on AWS
• Develop cloud-native applications using AWS Lambda, DynamoDB, S3, and related services
• Collaborate with architects, developers, and business stakeholders on technical solutions
• Gather requirements, provide project updates, and translate technical concepts to non-technical audiences
• Support testing, UAT, deployments, and CI/CD processes
• Lead projects, mentor junior developers, and perform code reviews

Requirements

• Bachelor’s degree in Computer Science, IT, or related field
• 5+ years of software development experience (6-8 preferred)
• Strong AWS Serverless and microservices experience
• Experience with Python and/or Node.js
• Frontend experience with React, React Native, JavaScript/TypeScript, and GraphQL
• Experience with CI/CD pipelines
• SQL and NoSQL database experience
• Proven ability to lead projects and mentor team members
• Recent U.S.-based project experience preferred

Nice to Have

• Jira
• Agile/Scrum experience
• Salesforce exposure

Key Projects

• Broadband platform development
• AI integration initiatives
• Mobile application enhancements
• Website re-platforming and API modernization
• Customer portal and vendor integrations

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Product Analyst | Remote (US) | Up to $100K + 10% Bonus

I’m partnering with a fast-growing digital health company used by millions of consumers worldwide that’s expanding its Product Analytics team.

We’re seeking a Product Analyst (2-4 years’ experience) who can become a trusted analytics partner to Product Managers and help elevate the company’s experimentation program.

What you’ll do: * Design, analyze, and optimize A/B tests * Partner closely with Product Managers on product decisions * Own Mixpanel/Amplitude analytics and reporting * Define event tracking requirements and measurement frameworks * Build dashboards and generate actionable product insights

What we’re looking for:

• 2-4 years of Product/Data Analytics experience
• Strong A/B testing experience from design through recommendations
• Mixpanel or Amplitude experience
• Strong SQL skills
• Experience working directly with Product teams
• Understanding of event tracking and instrumentation
• Direct-to-consumer product experience

Why join? * Fully remote within the US * High-impact role with significant Product exposure * Startup environment with strong financial backing * Opportunity to influence experimentation strategy at scale

Salary: Up to $100,000 base + 10% bonus

Work Authorization: U.S. Citizens and Green Card holders only. No sponsorship available.

Interested? Let’s connect.

#ProductAnalyst #ProductAnalytics #DataAnalytics #ABTesting #Mixpanel #Amplitude #SQL #RemoteJobs #HiringNow #DigitalHealthJobs

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About the Role

We are seeking a hands-on Senior Data Engineer to help design, build, and scale a modern cloud-based data platform that will serve as the foundation for analytics, reporting, operational insights, and future data initiatives across the organization.

This role is ideal for someone who enjoys operating at the intersection of data engineering, cloud architecture, data warehousing, and platform development. You’ll work closely with technical leadership to design and implement scalable data solutions, establish engineering best practices, and help shape the future direction of a growing data ecosystem.

This is not a maintenance-focused role. We are looking for builders who thrive in highly collaborative environments, enjoy ownership, and want the opportunity to influence architecture decisions in a greenfield setting.

What You’ll Do

• Design and build scalable cloud-native data pipelines and data integration frameworks.
• Develop and maintain ETL/ELT workflows supporting analytics and reporting needs across the business.
• Help architect and evolve a modern data warehouse environment.
• Build orchestration frameworks and workflow automation using Airflow.
• Develop robust data models supporting business intelligence, analytics, and downstream applications.
• Partner with stakeholders to understand requirements and translate them into scalable technical solutions.
• Improve data quality, observability, governance, monitoring, and platform reliability.
• Contribute to architecture decisions, engineering standards, and platform strategy.
• Support the implementation of modern cloud infrastructure and automated deployment practices.

Key Responsibilities

Data Engineering

• ETL/ELT pipeline development
• Workflow orchestration and scheduling
• Data modeling and warehouse design
• Batch and near real-time data processing
• Data quality and validation frameworks
• Data governance and security
• Performance optimization and scalability

Cloud & Platform Architecture

• AWS-based data platform development
• Cloud-native architecture design
• Infrastructure automation
• Monitoring and observability
• CI/CD and engineering best practices
• Data warehouse modernization
• Platform reliability and operational excellence

Analytics & Business Enablement

• Support enterprise reporting and analytics initiatives
• Build trusted datasets and semantic data models
• Partner with business stakeholders and analysts
• Enable self-service data consumption
• Improve accessibility and reliability of business-critical data

Desired Technical Experience

Data Engineering

• Python
• SQL
• Apache Airflow
• dbt
• ETL / ELT development
• Data modeling
• Data warehousing

Cloud & Infrastructure

• AWS
• S3
• Glue
• Redshift
• Lambda
• EMR
• Infrastructure as Code
• Terraform (preferred)

Data Platforms

• Snowflake
• Data lakes
• Data lakehouse architectures
• Data quality frameworks
• Workflow orchestration
• Monitoring and observability platforms

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About the Role

We are seeking a hands-on Principal or Senior Frontend Engineer to help build the next generation of AI-powered product experiences on top of large-scale knowledge systems and domain-specific datasets.

This role is ideal for someone who enjoys operating at the intersection of frontend engineering, AI-powered user experiences, product development, and platform architecture. You’ll work closely with technical leadership to design, build, deploy, and iterate on intelligent applications that leverage large language models, retrieval systems, recommendations, search, and AI-assisted workflows.

This is not a pure UI implementation role. We are looking for builders who can take ideas from concept to production, own the full user experience, and thrive in a fast-moving, high-ownership environment.

What You’ll Do

• Design and build AI-native user experiences that help users discover, consume, and interact with information more effectively.
• Develop frontend applications integrating LLMs, semantic search, recommendations, and AI copilots.
• Create highly performant React and TypeScript applications used by large audiences.
• Build rich interfaces that surface AI-generated insights, recommendations, summaries, and workflows.
• Partner closely with design, product, data, and engineering teams to rapidly validate concepts and ship new capabilities.
• Architect reusable frontend systems, design patterns, and shared component libraries.
• Influence frontend strategy, technical direction, and product architecture.
• Continuously improve performance, reliability, accessibility, observability, and user experience across the platform.

Key Responsibilities

AI-Powered Product Experiences

• AI copilots and assistants
• LLM-powered user interfaces
• Conversational experiences
• AI-assisted workflows
• Search and discovery experiences
• Recommendations and personalization
• AI evaluation and user feedback loops
• Prompt and interaction design

Frontend Architecture

• React and TypeScript application architecture
• Component systems and design systems
• State management patterns
• Micro-frontends (where appropriate)
• Performance optimization
• Accessibility and responsive design
• Testing and frontend quality frameworks
• Frontend observability and monitoring

Product Engineering

• User-facing product development
• Rapid prototyping and experimentation
• A/B testing frameworks
• Analytics-driven iteration
• Collaboration with product and design
• End-to-end feature ownership
• Customer-centric product development

Desired Technical Experience

Frontend

• React
• TypeScript
• Next.js
• JavaScript
• HTML5 / CSS3
• Frontend testing frameworks
• State management (Redux, Zustand, React Query, etc.)
• Design systems and component libraries

AI / ML Integration

• OpenAI, Anthropic, Gemini, or similar models
• AI-powered applications
• RAG-powered user experiences
• Semantic search systems
• Recommendations and retrieval systems
• AI copilots and assistants
• Prompt engineering and AI workflow design
• AI evaluation and feedback systems

Backend & APIs

• Python, Node.js, or similar backend technologies
• Django, FastAPI, Express, or related frameworks
• REST APIs
• GraphQL
• PostgreSQL
• Data integrations

Infrastructure

• AWS
• Docker
• Kubernetes
• CI/CD
• Frontend deployment pipelines
• Monitoring and observability platforms

Data

• PostgreSQL
• Redis
• Search platforms
• Analytics platforms
• Data visualization
• Event tracking and experimentation systems

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About the Company

Harnham is partnering with an established alternative finance company that has supported small and medium-sized businesses since 2008. The organization provides term loans ranging from $10,000 to $15 million and is known for a fast lending experience, with underwriting decisions and offers available the same day and funding available as soon as the following business day.

The company is transforming traditional small-business lending through AI-powered decisioning. Production AI agents are already operating across credit and underwriting workflows, supported by 18 years of proprietary credit data. With the first phase of the transformation approximately 70 percent complete, the organization is preparing to expand its AI capabilities into Sales, Customer Lifecycle, Finance, and Capital Markets.

The Opportunity

The AI Product Director will lead the next phase of an organization-wide AI transformation. Partnering closely with the Chief Credit Officer and executive leadership, this person will shape product design and roadmapping while translating strategic business priorities into AI products that deliver measurable operational and commercial results.

The Director will manage two AI Product Managers and oversee multiple product pods, with two to three initiatives typically running concurrently. Each initiative begins with understanding how the business operates today, identifying undocumented edge cases and workarounds, and reimagining the process from the ground up around AI.

Success requires a strong combination of product strategy, technical fluency, and hands-on delivery. The ideal candidate has contributed directly to AI solution design, participated in architecture decisions, and taken AI-enabled products from concept through production adoption.

What You Will Do

* Partner with executive leadership to translate business priorities into actionable AI product roadmaps.

* Lead product design and roadmapping across Credit, Sales, Customer Lifecycle, Finance, Capital Markets, and other business functions.

* Manage, coach, and develop two AI Product Managers while establishing consistent standards for discovery, design, documentation, and delivery.

* Oversee two to three concurrent AI product initiatives without compromising quality, stakeholder trust, or delivery outcomes.

* Lead discovery sessions with subject matter experts to map workflows, uncover edge cases, and understand operational workarounds.

* Reimagine business processes from first principles using AI rather than adding automation to existing workflows.

* Create detailed product specifications and design briefs for internal engineering teams and external development partners.

* Contribute directly to AI solution design, architecture discussions, evaluation approaches, and production-readiness decisions.

* Evaluate and select the appropriate engineering partner for each initiative.

* Manage external engineering partners against defined specifications, acceptance criteria, timelines, and quality standards.

* Establish evaluation frameworks using golden datasets, human review, deterministic checks, shadow testing, and other appropriate methods.

* Build compliance, explainability, auditability, and model-governance requirements into product designs before development begins.

* Lead quality control before products reach end users and measure results against clear preimplementation baselines.

* Partner with Data Science, Engineering, Technology, Risk, and functional leadership to support scalable and reliable AI products.

* Build trust with subject matter experts and functional leaders, address resistance thoughtfully, and drive adoption across the organization.

* Communicate product direction, progress, risks, tradeoffs, and measurable outcomes clearly to executive stakeholders.

What You Will Bring

* Eight or more years of product management experience, including leadership of complex AI, machine learning, or technology products.

* A demonstrated record of taking AI-enabled products from initial concept through production deployment and adoption.

* Experience reimagining a business process from the ground up using AI.

* Direct involvement in AI solution design, product architecture discussions, or technical blueprint creation.

* Practitioner-level understanding of generative AI, large language models, agentic patterns, orchestration, evaluation methods, hallucination mitigation, and golden datasets.

* Experience creating detailed product specifications or design briefs for engineering teams.

* Experience selecting, managing, and holding external engineering partners accountable to defined requirements.

* Proven ability to lead multiple concurrent product initiatives while maintaining delivery quality.

* Experience managing and developing Product Managers.

* Strong executive presence with the ability to influence functional leaders, communicate technical tradeoffs, and represent product direction independently.

* Working knowledge of responsible AI, model governance, explainability, and regulated decisioning.

* Familiarity with FCRA, ECOA, Regulation B, Fair Lending, adverse-action requirements, or comparable regulatory frameworks.

* Bachelor’s degree in Business, Computer Science, Engineering, Economics, or a related discipline.

Preferred Qualifications

* Product leadership experience within fintech, lending, payments, credit decisioning, risk technology, or another regulated financial environment.

* Experience working within a growing technology company where product leaders balance strategy with hands-on execution.

* Experience introducing AI products into established business workflows and leading the accompanying organizational change.

* Master’s degree in a relevant discipline.

Compensation and Workplace

The anticipated base salary range for this position is $275,000 to $300,000 per year. The final offer will depend on relevant experience, qualifications, specialized expertise, and other legitimate business considerations.

Additional performance-based cash compensation may be available. Relocation support may also be considered for qualified candidates.

The position requires two to three days onsite each week in the San Francisco Bay Area. The role will operate remotely until the company’s shared Bay Area workspace is finalized.

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Data Analyst II – Product Experimentation & Analytics

United States: Fully Remote

Compensation: USD $80,000-$100,000 base + 10% target bonus

Canada: Montreal, QC

Compensation: CAD $75,000-$95,000 base + 10% target bonus

Equity: None

Work Authorization (U.S.): U.S. Citizens and Green Card holders

About the Company

This growing consumer technology organization builds digital products designed to help people better understand and improve their health and wellbeing. The business is entering an important stage of growth, expanding its offering while investing more heavily in experimentation, analytics, and data-informed product development.

You’ll join a small, collaborative environment where Data works directly with Product and Engineering. Analysts are expected to go beyond reporting-asking the right questions, challenging assumptions, and using experimentation and user behavior data to influence what gets built next.

About the Role

The Data Analyst II will become a key analytics partner to the Product organization, with approximately 70% of the role focused on experimentation and 30% on broader product analytics.

This isn’t a role focused on building dashboards and responding to ad hoc requests.

You’ll partner directly with Product Managers to design experiments, determine how success should be measured, analyze results, and translate findings into recommendations that influence product decisions.

The initial priority is improving the quality and reliability of the existing experimentation program. From there, you’ll help scale the volume of testing while establishing stronger experimentation processes and measurement standards.

You’ll also take ownership of the team’s product analytics platform, partnering with Product and Engineering on event tracking, instrumentation, dashboards, and self-service analytics.

Key Responsibilities

• Partner directly with Product Managers throughout the experimentation lifecycle
• Design, measure, and analyze A/B tests and translate results into clear product recommendations
• Improve experimentation methodology, measurement quality, and decision-making
• Help scale a growing experimentation program while maintaining testing quality
• Own product analytics across Mixpanel or a comparable platform
• Define metrics and event-tracking requirements alongside Product and Engineering
• Establish new product events, requirements documentation, validation, and QA
• Build and maintain dashboards that enable Product teams to answer questions independently
• Analyze user behavior, conversion, engagement, and product performance
• Review historical experiments and identify opportunities to improve future testing
• Translate complex analysis into clear insights for technical and non-technical stakeholders

Must Haves

• 2-4 years of Product Analytics, Data Analytics, or similar experience
• Strong hands-on A/B testing and experimentation experience
• Experience owning experiments from initial design through analysis and recommendations
• Experience with Mixpanel, Amplitude, or a comparable product analytics platform
• Strong working knowledge of SQL
• Experience partnering directly with Product Managers
• Understanding of product instrumentation, event tracking, and metric definition
• Direct-to-consumer product experience
• Strong communication and stakeholder management skills
• Ability to turn analysis into clear product recommendations rather than simply presenting results

Nice to Have

• Mobile application analytics experience
• Experience working in a high-experimentation product environment
• Consumer health or digital health experience
• Experience improving or scaling an existing experimentation program
• Experience creating self-service product analytics environments

Why Join

• Become a core analytics partner to Product rather than operating as a reporting resource
• Own experimentation from initial hypothesis through product recommendation
• Help improve and scale an experimentation program at an important stage of growth
• Work directly with Product and Engineering on how user behavior is measured
• Have meaningful influence over product decisions within a small, highly collaborative team
• Work on a consumer-facing digital product where experimentation directly impacts the user experience

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Private Cloud Architect

Location: Dallas, TX

Work Model: Onsite – 5 days per week

Compensation: $200,000-$210,000 base + bonus + equity

About the Company

This established enterprise organization is making a significant investment in modernizing its infrastructure and building a next-generation private cloud platform.

The goal is to bring public-cloud-style capabilities into the data center-giving engineering teams secure, automated, self-service access to compute, storage, networking, and platform services while creating a consistent experience across private and public cloud environments.

The engineering culture values technical ownership, automation, strong architectural judgment, and leaders who remain close to the technology while defining long-term platform direction.

About the Role

This is a senior, hands-on architecture role responsible for defining and evolving an enterprise private cloud platform.

You’ll lead the transition from traditional data center infrastructure toward a modern, software-defined platform built around Kubernetes, Infrastructure as Code, automation, APIs, and self-service capabilities.

A major part of the mandate is creating an internal cloud experience that gives developers the speed and usability they expect from public cloud while maintaining the control, performance, security, and reliability required within an enterprise data center.

You’ll also shape how private infrastructure integrates with AWS, Azure, and GCP to create a cohesive hybrid cloud architecture.

Key Responsibilities

• Define the architecture and long-term strategy for enterprise private cloud infrastructure
• Design cloud-native platforms across compute, storage, networking, and shared platform services
• Build and evolve Kubernetes-based environments using OpenShift, Rancher, or comparable technologies
• Develop self-service infrastructure capabilities through APIs, automation, and developer-friendly interfaces
• Design hybrid architectures connecting private infrastructure with public cloud environments
• Establish Infrastructure as Code and automation standards using Terraform or similar technologies
• Architect highly available and resilient distributed infrastructure at enterprise scale
• Modernize legacy infrastructure and transition workloads toward cloud-native architectures
• Design infrastructure capable of supporting high-performance computing and GPU-intensive workloads
• Partner with networking, security, SRE, and application engineering teams on end-to-end platform architecture
• Establish platform governance, security, observability, and operational standards
• Provide architectural leadership while remaining technically close to implementation

Must Haves

• 8+ years of infrastructure, cloud, platform engineering, or architecture experience
• Deep experience designing private cloud or large-scale data center infrastructure
• Strong Kubernetes experience, ideally including OpenShift or Rancher
• Experience designing hybrid architectures spanning on-premises infrastructure and AWS, Azure, or GCP
• Strong Infrastructure as Code and automation experience, including Terraform
• Experience designing highly available, scalable distributed systems
• Strong understanding of compute, storage, networking, and platform infrastructure
• Experience with CI/CD, GitOps, and infrastructure automation
• Ability to define architecture while remaining technically hands-on
• Experience modernizing established enterprise infrastructure rather than exclusively working in public cloud

Nice to Have

• Internal developer platforms, private cloud portals, or self-service infrastructure
• Advanced data center networking, including L2/L3 architecture and segmentation
• EVPN/VXLAN or software-defined networking
• Kafka, Spark, Flink, or similar distributed data technologies
• GPU or HPC infrastructure
• Grafana, Prometheus, and modern observability platforms
• IAM, identity integration, or Zero Trust architecture
• Microservices architecture
• Experience operating across multiple public cloud providers

Why Join

• Architect a private cloud platform rather than simply maintain traditional infrastructure
• Build an internal cloud experience that brings automation and self-service capabilities into the enterprise data center
• Own major architectural decisions across Kubernetes, compute, storage, networking, automation, and hybrid cloud
• Lead the modernization of legacy infrastructure into scalable cloud-native platforms
• Remain technically hands-on while having significant influence over long-term platform strategy
• Work on complex infrastructure challenges including hybrid cloud, distributed systems, GPU/HPC workloads, and advanced networking

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Lead Data Scientist

$140,000-$150,000 + 10% bonus

Overview

A growing organisation is seeking an experienced Lead Data Scientist to drive strategic analytics initiatives across customer experience, operational efficiency, asset performance, and cost optimisation. This highly visible role partners closely with senior business leaders to identify challenges, develop data-driven solutions, and influence decision-making through advanced analytics and predictive modelling.
The ideal candidate combines deep technical expertise with strong business acumen, excels at communicating complex concepts to non-technical audiences, and has a proven track record of leading projects from concept through implementation with minimal supervision.

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Key Responsibilities

Project Leadership & Stakeholder Management

• Build trusted relationships with senior stakeholders, including director- and executive-level leaders.
• Independently lead projects from problem definition through deployment and performance monitoring.
• Facilitate intake sessions, define project scope, estimate effort, manage priorities, and communicate progress effectively.
• Mentor and guide junior analysts and data scientists on methodology, project structure, and technical execution.
• Present findings and recommendations to leadership teams, including executive audiences.

Advanced Analytics & Data Science

• Develop and deploy predictive models using machine learning techniques such as gradient boosting, ensemble methods, decision trees, and other supervised and unsupervised learning approaches.
• Design segmentation frameworks using clustering and classification techniques.
• Conduct statistical analysis, model validation, back-testing, and performance measurement to ensure reliability and business value.
• Identify patterns, root causes, and opportunities through large-scale data analysis.
• Develop innovative analytical approaches to improve insight generation and operational effectiveness.
• Support business decision-making through forecasting, scoring models, optimisation techniques, and operational analytics.

Data Management & Process Improvement

• Gather, reconcile, clean, validate, and integrate data from multiple internal and external sources.
• Establish data quality standards and controls to improve accuracy and consistency.
• Design and implement processes that reduce risk, improve efficiency, and create measurable business value.
• Monitor and assess the ongoing performance of implemented analytical solutions.

Executive Communication

• Translate complex analytical findings into actionable business recommendations.
• Develop compelling executive presentations and data-driven narratives that influence organisational strategy and operational improvements.

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Required Qualifications

• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Engineering, Economics, Computer Science, or a related discipline.
• 10+ years of experience in data science, advanced analytics, predictive modelling, risk analytics, or a related quantitative function.
• 3+ years of hands-on Python experience building machine learning, forecasting, regression, classification, and segmentation models.
• 3+ years of advanced SQL experience, including optimisation of complex queries across large datasets.
• Strong expertise in statistical methods, probability theory, experimental design, predictive analytics, sampling techniques, and model evaluation.
• Demonstrated experience analysing large structured and unstructured datasets.
• Experience presenting analytical insights to executive audiences and influencing strategic decisions.
• Ability to communicate complex technical concepts to business stakeholders with varying levels of analytical expertise.
• Strong project management, prioritisation, and multitasking skills.
• Proven ability to work independently in a fast-paced, evolving environment.
• Experience sourcing, validating, and integrating data from multiple systems and platforms.

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Preferred Qualifications

• Master’s degree in a quantitative discipline.
• Experience in risk management, portfolio analytics, financial modelling, or asset performance analysis.
• Experience using consumer, credit, demographic, or third-party external datasets.
• Prior experience developing scoring models, predictive risk models, or decision-support frameworks.
• Experience within highly regulated industries where model governance, validation, and audit requirements are critical.
• Familiarity with model risk management frameworks and third-party model review processes.
• Experience working with cloud-based data and analytics environments, including object storage and large-scale compute platforms.
• Experience with modern data warehouse technologies.

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