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Director of Analytics

We’re looking for a hands-on Director of Analytics to lead the strategy, architecture, and delivery of our global analytics platform – serving both internal stakeholders and thousands of clients worldwide. This is a builder’s role: you’ll personally shape data pipelines, semantic models, and embedded analytics products while building and mentoring a high-caliber engineering team.

Role Details

• Own the multi-year roadmap for a global analytics platform spanning internal BI and external client-facing reporting
• Lead architecture decisions across data warehousing (Snowflake, Azure DataLake), semantic modeling (LookML, dbt), and BI tools (Looker, Power BI)
• Design embedded analytics applications integrated directly into product experiences
• Build, recruit, and mentor a team of analytics engineers working across the full data lifecycle
• Establish data governance, observability, and SLAs for data freshness and pipeline reliability
• Partner with executive leadership and clients to translate business needs into analytics capabilities

Qualifications

• 10+ years in analytics/data engineering; 5+ years leading and growing technical teams
• Proven track record delivering both internal and client-facing analytics products
• Deep expertise with Snowflake and fluency across at least two major cloud providers (AWS, Azure, GCP)
• Expert-level SQL, hands-on dbt experience, and strong Python skills
• Experience with embedded analytics (React/Vue.js), semantic modeling, and data governance frameworks (RBAC, lineage, compliance)
• Preferred: travel/hospitality industry experience, multi-tenant platform experience, IaC (Terraform, Docker, Kubernetes), advanced degree

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Senior Full-Stack Software Engineer | AI & Predictive Analytics

$190K-$225K Base + 20% Bonus | Up to ~$270K Total Compensation
New York City | Atlanta | Chicago | Dallas | Fort Washington, PA

I’m partnering with a Blackstone-backed organization operating one of the largest portfolios in its industry to hire a Senior Software Engineer into a small, highly entrepreneurial Innovation team.

This is a rare opportunity to get startup-level ownership with the resources, data and scale of a major enterprise.

The team is building an AI-enabled investment and predictive analytics platform designed to fundamentally change how billions of dollars in assets are evaluated and managed. The product is already in production, with significant ambitions around predictive modeling, AI-enabled workflows and sophisticated decision-support tooling.

You’ll operate as a core engineer within a small product team, partnering directly with Product, Design and a sophisticated Research & Analytics organization. The mandate is genuinely end-to-end: understand the business problem, shape the product, architect the solution, build it and put it into the hands of investment professionals.

What They’re Looking For

• 4+ years of software engineering experience
• Strong Python development expertise
• Modern full-stack engineering experience; React/Node preferred, but adjacent technologies welcomed
• Experience building and shipping production-grade products end-to-end
• Exposure to AI/ML, predictive analytics or data science-driven products
• Ideally experience productizing models or building tools used by investors/financial professionals
• Background in fintech, investment technology, financial services, analytics-heavy products or similarly sophisticated environments
• Comfortable operating in a 0→1 / early-stage / venture-incubation environment
• Strong product instincts and ability to communicate directly with senior business stakeholders
• Backend- or frontend-leaning engineers are absolutely considered, provided you’re comfortable contributing across the product

Why It’s Compelling

This isn’t another engineering seat buried inside a large organization. You’ll have outsized ownership and visibility, working on a platform with executive sponsorship and the potential to reshape a core investment workflow.

For someone who wants to combine full-stack engineering, AI, predictive analytics and investment technology, while retaining the speed and ownership of an early-stage team, it’s an unusually compelling opportunity.

Compensation: $190K-$225K base + 20% performance bonus, with total compensation reaching approximately $270K at the top of the band.

Locations: NYC, Atlanta, Chicago, Dallas or Fort Washington, PA. Hybrid/on-site approximately 3-4 days per week, with periodic travel to NYC for team collaboration.

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Senior Data Analyst – Marketing Science | London

£60,000-£75,000 | Hybrid | London

We’re hiring a Senior Data Analyst to join a growing Marketing Science team within a leading customer experience agency.

You’ll work across marketing analytics, customer journey analysis, campaign effectiveness and digital analytics, turning data into clear insights that influence client and business decisions.

What you’ll be doing:

• Lead analytics projects and take ownership of delivery
• Analyse campaign and customer journey performance
• Use SQL and/or Python to generate actionable insights
• Work with tools such as GA4, Adobe Analytics or similar
• Build and develop dashboards and reporting
• Present findings to clients and senior stakeholders
• Help shape analytics roadmaps and identify opportunities for growth
• Mentor and support junior analysts

What we’re looking for:

• 4+ years’ experience in analytics/marketing analytics
• Strong agency experience
• Hands-on experience with digital/web analytics tools
• Good SQL and/or Python skills
• Strong stakeholder and communication skills
• A curious, commercially minded approach to analytics
• Experience supporting or mentoring junior analysts

There is a particular opportunity for someone with a strong digital/web analytics background, including GA4 or similar, to work on a major automotive client.

Hybrid: 3 days office / 2 days WFH
Location: London
Salary: £60k-£75k

Interested? Find out more and apply via the link below!

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About the Role

This is a high-visibility, high-impact individual contributor role sitting at the intersection of machine learning, clinical data science, and translational biology. You will lead the company’s drug response prediction work – one of the most consequential and technically demanding initiatives in our portfolio.

This is not a pure research role, and it is not a pure engineering role. It requires someone who can move fluidly between rigorous quantitative analysis and the realities of working with large, messy, real-world datasets – someone who can apply state-of-the-art methods without losing sight of what actually works in practice.

The Problem We’re Solving

There are thousands of drugs that work – but only for a small subset of patients, and we largely don’t know why. We are building a systematic engine of understanding between drugs and biology: one that can decode the relationship between a patient’s biology and their response to treatment, and translate that into insights that immediately improve care.

This is foundational, mission-critical work. The person in this role will directly shape how we approach this problem – the methods we use, the data we bring to bear, and the analytical frameworks we build. It is an opportunity to have genuine scientific and clinical impact.

What You Will Do

Drug Response Prediction

• Lead the design and execution of computational approaches to predict drug response across patient populations
• Develop and validate predictive models using real-world clinical data, integrating diverse data modalities
• Identify biological and clinical signals that differentiate responders from non-responders
• Translate modeling outputs into actionable biological and clinical insights

Data & Analysis

• Work extensively with real-world data (RWD) – EHR, claims, clinical trial data – at scale
• Build robust analytical pipelines that handle messy, heterogeneous, and incomplete data
• Apply appropriate statistical frameworks to ensure rigor and reproducibility
• Contribute to the development and evolution of internal data infrastructure and analysis tooling

Modeling & Methods

• Apply and adapt state-of-the-art ML methods – including causal inference, survival analysis, and multi-omics integration – to biological and clinical problems
• Balance methodological sophistication with practical performance constraints
• Evaluate trade-offs between model complexity, interpretability, and real-world utility
• Stay current with the literature and bring relevant advances into the team’s practice

Cross-Functional Collaboration

• Work closely with biologists, clinical scientists, and data engineers to design studies and interpret results
• Communicate findings clearly across both technical and non-technical audiences
• Contribute to a collaborative, intellectually rigorous team culture

What We’re Looking For

Required

• PhD in a quantitative discipline – computational biology, biostatistics, bioinformatics, computer science, physics, statistics, or a related field; open to diverse backgrounds
• Fluent in Python – comfortable writing clean, well-structured code for data analysis and modeling
• Real-world data experience – hands-on work with EHR, claims, or other large-scale clinical datasets
• Ability to work with messy data at scale – experience wrangling, cleaning, and extracting signal from imperfect data
• Strong quantitative intuition – both in modeling design and in interpreting results critically
• Industry experience – 4+ years; 6+ preferred, ideally with both large pharma/biotech and startup exposure
• Mission-driven – genuinely motivated by the opportunity to improve patient outcomes through better science

Strongly Preferred

• Experience with causal inference methods (propensity scoring, instrumental variables, difference-in-differences, etc.)
• Background in statistics, epidemiology, or biostatistics alongside ML
• Familiarity with pharmacogenomics, multi-omics, or translational biology
• Experience contributing to or extending data infrastructure and analysis frameworks
• Track record of working across interdisciplinary teams (biology, chemistry, clinical)
• Startup experience – comfort with ambiguity, ownership, and moving quickly

Background & Experience Profile

We are open to a wide range of PhD backgrounds – what matters most is strong quantitative and analytical foundations, genuine intellectual curiosity, and the ability to work rigorously with complex biological and clinical data. Prior biology experience is not required, but candidates with some exposure to biological or clinical domains will be viewed favorably.

The ideal candidate has spent time in both large pharma/biotech (where they developed rigor and depth) and a startup environment (where they developed speed and ownership). If you haven’t done both, a trajectory that moves toward increasing independence and scope is what we’re looking for.

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Senior Product Analyst

US Remote

$90,000 – 105,000 Base Salary

We’re partnering with one of the world’s most downloaded wellness apps on a Senior Product Analyst hire. This role sits at the center of how a top consumer app understands its users, tests its ideas, and decides what to build next.

The role:

You’ll sit within the Data team and act as the analytical partner to Product, owning experimentation, product analytics, and insight generation from event-level data. You’ll work day to day with Product Managers, User Acquisition, and Engineering.

You will:

• Design, analyze, and interpret A/B tests and experiments that guide product decisions
• Own product analytics reporting from event-level data, covering feature performance, funnels, retention, and user behavior
• Partner with PMs and Engineers to define metrics, success criteria, and measurement plans for new features
• Turn behavioral insights into clear, actionable product recommendations
• Build self-serve dashboards that give Product and leadership visibility into performance
• Work with the wider Data team on data quality, definitions, and event-data modelling
• Champion experimentation and data-informed decision-making across the organization

What we’re looking for:

• 1 to 3 years as a product analyst, data analyst, or similar, ideally in consumer apps or subscription products
• Hands-on experience with an event-tracking/product analytics platform (Mixpanel, Amplitude, or similar)
• Strong SQL and comfort working with large datasets
• Experience with BI tools (Looker, Tableau, Omni, or similar)
• Experience designing and analyzing A/B tests
• Strong communication skills: you translate data into narratives PMs and executives act on
• Comfortable with ambiguity and cross-functional work

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Staff Product Analyst

Location: San Francisco (Remote Eligible)

Salary: $200K-$240K base + Equity

We’re hiring a Staff Product Analyst for a hyper-growth, Series E AI company valued at $3B+. This is an opportunity to play a key role in shaping product strategy and growth by leveraging data to drive decisions, optimize user experiences, and unlock new opportunities.

What You’ll Do:

• Shape product strategy with data-driven insights – Define key metrics, track user behavior, and identify trends that impact engagement and retention.
• Deep-dive into user journeys – Uncover friction points and growth levers to enhance adoption, conversion, and retention.
• Optimize experimentation and A/B testing – Design and analyze tests to improve product features, pricing, and personalization strategies.
• Develop self-service analytics tools – Build dashboards and automated reporting to empower teams with real-time data.
• Partner with Product, Engineering & Leadership – Translate complex data into clear, actionable recommendations to improve product performance and business outcomes.

What We’re Looking For:

• 7+ years of experience in Product Analytics, preferably within high-growth tech companies.
• Expert SQL skills and experience working with large-scale product datasets.
• Proficiency in Python or R, with a strong foundation in statistical analysis and experimentation.
• Hands-on experience with A/B testing methodologies and user segmentation.
• Experience with ELT data modeling and BI tools like Looker, Omni, or Hashboard.
• Strong executive communication skills, with the ability to influence product decisions through data.
• Thrives in a fast-paced, high-impact environment, with a passion for uncovering insights that drive product growth.

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Staff Growth Product Analyst

US Remote

$200-240k base + equity

About the Role:

We’re looking for a Staff Growth Product Analyst to drive impactful growth analytics for an innovative AI-driven development platform that’s transforming how developers create and deploy user interfaces. Leveraging cutting-edge AI technologies, this platform enables rapid prototyping and significantly accelerates product development, enhancing user growth, engagement, and overall developer experience.

Role Highlights:

• Deep dive into user behaviors, journeys, and growth funnels to uncover opportunities for enhanced engagement and acquisition.
• Generate actionable insights aimed at boosting critical growth metrics like DAU, MAU, and user retention.
• Design, execute, and analyze A/B tests to drive informed decision-making and product improvements.
• Influence strategic decision-making through rigorous data analysis and compelling recommendations.
• Collaborate cross-functionally with product managers, engineers, data scientists, and growth marketers to drive continuous product improvement and iteration.

Who You Are:

• You have 7+ years of proven expertise in growth and product analytics, ideally within early-stage or innovation-driven product environments.
• You’re adept at conducting thorough funnel analyses, spotting rapid experimentation opportunities, and recommending actionable product enhancements.
• You thrive on solving complex analytical problems with high energy and intellectual rigor.
• Experienced with modern data stack (e.g., Snowflake, dbt, Preset, Hashboard, Kafka, Fivetran, Omni, Hex, Sigma, SQL, Python).
• You have previous experience (or a strong interest) in working with AI or machine learning-driven products.

Ideal Fit: You’re a driven, collaborative analytics expert passionate about influencing groundbreaking products. Excited by high-paced, innovative environments, you’re motivated by measurable impact and shaping the future of developer-focused, AI-powered technologies.

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Senior Data Platform Engineer

Location: Los Angeles, CA

Salary: $160-200k base

We’re partnering with a fast-scaling, mission-driven advanced technology company building complex software and hardware systems deployed in real-world environments. Their platform processes and operationalizes high-volume data to power critical decision-making across the organization.

They are hiring a Senior Data Platform Engineer to design and scale the core data infrastructure that supports company-wide operations.

The Role

As a Senior Engineer on the Data Platform team, you will:

• Design and build scalable data pipelines and transformation frameworks
• Own ingestion and egress systems that unify multiple operational data sources
• Develop reliable, secure data models that power internal data products and applications
• Partner with engineering, product, and operations to translate business needs into production-grade systems
• Advocate for best practices across testing, CI/CD, data modeling, and security
• Debug and optimize complex transformation pipelines in production environments

What They’re Looking For

• 5+ years of experience in data engineering or backend engineering
• Strong programming skills in Python or similar languages
• Experience with Spark, PySpark, SQL, and dbt
• Familiarity with large-scale data platforms and cloud environments (AWS, Azure, or GCP)
• Experience with containerization and modern deployment practices
• Ability to operate autonomously in fast-moving environments
• Strong ownership mindset and attention to security best practices
• Must be a U.S. Person due to export-controlled information requirements

This is a high-impact role focused on building durable data systems that directly support operational execution at scale.

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Data Engineer

Location: Redwood City, CA (Hybrid – Tuesday, Wednesday, Thursday)

Salary: $120-150k base + Equity

Harnham has partnered with a Series B PropTech startup on a mission to make quality housing more affordable and accessible. Fresh off a new funding round and backed by leading investors, the company is scaling operations and entering new markets. With that growth, their data demands have outpaced the current team, and they now need a dedicated Data Engineer.

The Role

This hire will own the company’s data from end to end: understanding the source systems, building and maintaining the core datasets the business trusts, and turning raw operational data into clear, decision-ready outputs. They will work closely with Finance, Operations, and leadership to keep data accessible and useful as the company grows.

Responsibilities:

• Own the data pipelines: take responsibility for a portfolio of existing production ETL pipelines, handling daily maintenance, monitoring, and reliability so stakeholders can trust the data
• Design and build new pipelines: architect scalable ETL/ELT workflows that ingest data from new sources and grow with increasing data volume and complexity
• Build and own core datasets: design and maintain the sources of truth for business reporting and decision-making
• Master the source systems: ERP, CRM, project management, and finance platforms (NetSuite, Salesforce, and similar operational tools), understanding how data maps to real business processes
• Democratize data access: deliver well-documented, self-service-ready data products for Finance, Ops, and go-to-market teams
• Expand analytical coverage: identify opportunities for new tables, metrics, and derived datasets that unlock insight
• Set the standards: evolve data modeling, testing, documentation, and ownership practices from the ground up

The Ideal Candidate

• 2-4 years as a Data Engineer, building core datasets and supporting business teams
• Proven ETL and data pipeline ownership: experience building, maintaining, and monitoring production pipelines end to end, not just contributing to someone else’s
• Advanced SQL and strong data modeling skills, with experience designing analytical models that support real reporting and analytics use cases
• Hands-on experience shipping scalable cloud data solutions (AWS, Databricks, dbt) across methodologies like dimensional modeling, data marts, or medallion architecture
• Comfort tracing data through source systems and multiple layers of transformation
• A fast learner’s mindset: thrives in environments where priorities evolve and there’s always a new system or domain to pick up

Bonus points for:

• Integrating financial/ERP/CRM/payment systems (NetSuite, Salesforce, or similar)
• Aggregating from diverse sources, including APIs, geospatial imagery, unstructured web data, and public government records
• Exposure to feature engineering, forecasting, or AI-adjacent analytics
• Curiosity about AI tooling. No expertise needed, just a willingness to work smarter with it

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Product Marketing Manager – Mobile Gaming

Location: Miami, FL (Hybrid)

Salary: $140,000-170,000

Job type: Full-time, Permanent

We’re partnering with a leading mobile game studio in Miami, part of a major international gaming group, to hire a Product Marketing Manager for its flagship title.

This is a rare opportunity to own the full player journey for one of the most recognizable games in its genre, from first ad impression to long-term retention, and turn new content launches into viral cultural moments.

Why This Role?

You’ll be the bridge between the development team and millions of players, owning full-funnel marketing strategy for a chart-topping mobile game. You’ll shape how new features and content packs go to market, drive aggressive organic growth, and lead expansion into new international markets, with real budget ownership and cross-functional influence from day one.

What You’ll Be Doing

• Define target audiences using player data, user research, and community insight, and dig into what’s driving unexpected player trends
• Shape product positioning and brand narratives that turn content updates into must-play moments, backed by competitive analysis and market research
• Design and execute full-funnel go-to-market (GTM) plans that integrate product features with user acquisition (UA), owning budgets and success metrics along the way
• Lead user acquisition and retention campaigns across paid, organic, PR, social, and non-traditional channels, including live events, influencer partnerships, and referral programs
• Build co-marketing and collaboration strategies with influencers, IPs, and consumer brands, coordinating cross-functional teams across product, paid UA, data science, and creative
• Partner with ASO and creative teams to optimize the App Store funnel, listings, and featured placements
• Own CRM and lifecycle marketing strategy to keep every player segment engaged
• Measure marketing impact through incrementality analysis, brand lift studies, and marketing mix modeling (MMM), using the data to optimize spend

What You’ll Bring

• 5+ years of product marketing experience in gaming or entertainment (mobile gaming strongly preferred)
• Bachelor’s degree or MBA in Marketing or a related field
• A proven track record of product marketing strategies and activations that delivered measurable growth
• Fluency in mobile gaming metrics (LTV, retention curves, ROAS, CPI) and the ability to turn analytics into action
• Strong cross-functional leadership: you can align developers, data scientists, and creatives around one goal
• A genuine passion for games and a sharp read on industry trends and the psychology of player engagement

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Staff Data Scientist, Finance – Consumption Forecasting

Location: San Francisco or New York | Hybrid (3 days per week in office)

Salary: $240-300k base + bonus + equity (RSUs)

This is a rare chance to own forecasting infrastructure at the center of a high-growth, consumption-based developer platform, one that powers some of the world’s most dynamic applications and scales with every developer and enterprise building on it.

As a consumption-based business, forecasting usage across compute, bandwidth, edge, and storage isn’t a support function. It’s foundational to how we plan infrastructure, revenue, and long-term strategy. This role exists to lead that work at the highest level.

What you’ll own

This is a senior individual contributor role with organization-wide impact. You’ll define forecasting methodology, build systems that scale with a rapidly growing platform, and sit at the intersection of Finance, Infrastructure, Product, and GTM with direct visibility to executive leadership.

• Own production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration from first principles to live system
• Build forecasting systems that account for usage-based pricing dynamics, consumption patterns, and customer lifecycle across the platform, built for how this business actually works, not retrofitted SaaS models
• Design hierarchical forecasting models across account, cohort, segment, and global aggregate levels, covering operational, quarterly, and long-range planning cycles
• Establish backtesting, monitoring, and explainability standards that make forecast accuracy transparent and defensible
• Build scenario simulation frameworks to evaluate pricing changes, packaging adjustments, and product launches
• Partner with Finance on board-level reporting, with Infrastructure Engineering on capacity planning, and with Product and GTM on adoption curves and usage drivers
• Set forecasting best practices across the broader Data organization

What we’re looking for

• 7+ years in data science, quantitative analytics, or applied statistics at senior or staff level
• Deep expertise in time-series forecasting and statistical modelling in a usage-based or SaaS environment
• Proven track record building and productionizing ML systems at scale
• Strong Python and SQL, with experience on large-scale usage and billing datasets
• Familiarity with probabilistic modelling, hierarchical forecasting, and causal inference
• Experience partnering with Finance or executive leadership on planning cycles
• Comfortable operating autonomously in fast-moving, ambiguous environments

Nice to have

• Background in cloud infrastructure, developer tools, or consumption-based revenue models
• Familiarity with modern data stacks: Snowflake, Delta Lake, dbt, Airflow
• Prior technical mentorship or informal leadership experience

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Senior Data Engineer

San Francisco, CA

$180-240K base + equity

We’re partnered with one of the most recognized developer platforms in the world, trusted by engineering teams at OpenAI, Meta, Netflix, and Adobe, who are scaling their data platform and looking to hire a Senior Data Engineer to own the pipelines and foundations at the core of their data ecosystem.

You’ll own the full pipeline lifecycle, from ingestion architecture through to analytics-ready data, working closely with Data Platform Engineers and partnering with analysts and data scientists who depend on what you build every day.

What you’ll do

• Design and build scalable ingestion pipelines and orchestration frameworks across structured, semi-structured, and event-based sources
• Own reliability, observability, and performance across the full pipeline lifecycle from raw ingestion to analytics-ready delivery
• Build and maintain dbt transformation pipelines serving as the single source of truth across Finance, Product, GTM, and Engineering
• Ensure revenue and billing data meets the accuracy and auditability required for public company reporting, including SOX compliance
• Apply software engineering principles throughout: CI/CD, testing, observability, version control, and automation
• Enable self-serve analytics through semantic layer development, strong abstractions, and clear documentation
• Champion data quality and governance across classification, ownership, access policies, and data lifecycle management

What we’re looking for

• 5+ years in data engineering or a hybrid data/analytics engineering role, with a track record of owning pipelines end-to-end in high-growth or enterprise environments
• Advanced SQL and dbt (Core or Cloud), Snowflake or comparable cloud data warehouse, Python, and Airflow
• Experience with Kafka and streaming data systems, with working knowledge of ClickHouse, Iceberg, or similar technologies
• Experience with ingestion tools such as Fivetran, Airbyte, or Polytomic
• Cloud-native architecture experience across AWS, GCP, or Azure
• Exposure to designing data systems that meet compliance and governance requirements, including SOX or equivalent
• Strong communication and collaboration skills, with the ability to contribute as a technical voice across engineering and business stakeholders

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