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Staff Data Scientist (Product)

Location: Remote

Salary: $190-220k

We’re partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role embedded in their product organization. This is for someone who combines deep statistical expertise with the ability to influence how an entire company makes decisions – not just someone who runs experiments, but someone who builds the culture and infrastructure around them.

What You’ll Be Doing

• Owning and advancing the company’s experimentation roadmap, focused on high-leverage product questions around customer workflows, churn risk, and long-term value
• Designing and analyzing complex A/B tests, multivariate experiments, and Bayesian methods to measure the real impact of product changes
• Applying causal inference techniques (DiD, synthetic control, propensity score matching, instrumental variables) where traditional RCTs aren’t feasible
• Building and governing a unified KPI framework that connects product health metrics to meaningful business outcomes
• Partnering with Data Engineering to build scalable, self-serve experimentation tooling and reusable analytical frameworks
• Translating complex statistical findings into clear, compelling narratives for VP and C-suite audiences
• Mentoring and training junior and mid-level data scientists on experimental design and causal modeling

What We’re Looking For

This is a senior individual contributor role reporting to the Director of Product Data, acting as a strategic thought partner across Product, Engineering, Finance, Design, and Product Marketing. The company is at an inflection point in how it uses data to make product decisions, and this person will be central to shaping that.

Essential:

• 6+ years in applied data science, economics, or product analytics
• Proven expertise in causal inference: DiD, PSM, instrumental variables, quasi-experimentation
• Deep experience in A/B testing methodology including sequential testing, CUPED, variance reduction, and network effects
• Advanced SQL and Python or R for statistical modeling
• Experience with Snowflake or similar cloud data warehouses
• Exceptional communication skills, comfortable presenting to and influencing C-suite stakeholders
• Demonstrated ability to drive change in organizations where experimentation culture is still developing

Nice to have:

• Experience with dbt, Airflow, or Databricks
• Background in SaaS and product data science

To Apply for this Job Click Here

To Apply for this Job Click Here

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

To Apply for this Job Click Here

To Apply for this Job Click Here

Staff GTM Data Scientist

Location: Remote

Salary: $190-220k base

We’re partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role sitting at the heart of their product and go-to-market strategy. This isn’t a reporting role or a dashboard-builder position. It’s for someone who can drive a genuine shift toward data-driven decision making across the organization, and who has the technical depth and communication skills to bring leadership along with them.

What You’ll Be Doing

• Owning and advancing the company’s experimentation roadmap, focusing on high-leverage questions around customer workflows, churn risk, and long-term value
• Designing and analyzing complex A/B tests, multivariate experiments, and Bayesian methods to assess the real impact of product and business changes
• Applying causal inference techniques (DiD, synthetic control, propensity score matching, instrumental variables) where traditional RCTs aren’t feasible
• Building and governing a unified KPI framework that connects product health metrics to business outcomes
• Partnering with Data Engineering to build scalable, self-serve experimentation tooling and reusable analytical frameworks
• Translating complex statistical findings into clear, compelling narratives for VP and C-suite audiences
• Mentoring and training junior and mid-level data scientists on experimental design and causal modeling

What We’re Looking For

This is a senior individual contributor role reporting to the Director of GTM Data, acting as a strategic thought partner across Product, Marketing, Finance, and Engineering. The company is at an inflection point in how it uses data, and this person will be central to shaping that.

Essential:

• 6+ years in applied data science, economics, or product analytics
• Proven expertise in causal inference: DiD, PSM, instrumental variables, quasi-experimentation
• Deep experience in A/B testing methodology including sequential testing, CUPED, variance reduction, and network effects
• Advanced SQL and Python or R for statistical modeling
• Experience with Snowflake or similar cloud data warehouses
• Exceptional communication skills, comfortable presenting to and influencing C-suite stakeholders
• Demonstrated ability to drive change in organizations where experimentation culture is still maturing

Nice to have:

• Experience with dbt, Airflow, or Databricks
• Background in SaaS and product data science

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior Data Scientist – Growth & Customer Analytics

Remote – US

Compensation up to 200K

We are seeking a Senior Data Scientist to help drive customer growth, retention, and lifecycle optimization through advanced analytics and machine learning.

This role sits at the intersection of Data Science, Product, Marketing, and Customer Success, leveraging data to improve customer acquisition, engagement, retention, and expansion strategies. The successful candidate will play a key role in developing predictive models, customer segmentation frameworks, and experimentation strategies that directly influence business performance.

Responsibilities:

• Develop and deploy predictive models focused on customer churn, retention, expansion, and lifetime value
• Build customer segmentation frameworks to better understand user behavior and support personalized engagement strategies
• Partner closely with Marketing, Product, Revenue, and Customer Success teams to identify growth opportunities and optimize customer journeys
• Analyze customer lifecycle performance and identify opportunities to improve acquisition, activation, engagement, retention, and expansion metrics
• Design and evaluate A/B tests and experiments to measure the effectiveness of marketing campaigns, product initiatives, and customer engagement programs
• Translate complex analytical findings into actionable recommendations for both technical and non-technical stakeholders
• Develop forecasting models and business insights that support strategic decision-making
• Collaborate with Data Engineering and Analytics teams to ensure scalable and reliable data solutions
• Influence business strategy through data-driven insights and measurable outcomes.

Requirements

• Master’s or PhD in Statistics, Mathematics, Data Science, Computer Science, Economics, Operations Research, or a related quantitative discipline
• 4+ years of experience in Data Science and Applied Machine Learning, alongside areas like Customer Analytics, Marketing Analytics, or a related field
• Strong experience building predictive models focused on churn prediction, customer retention, customer lifetime value, propensity modeling, or expansion opportunities
• Expertise in customer segmentation techniques, clustering methodologies, and behavioral analytics
• Strong understanding of experimentation, causal inference, and statistical analysis
• Advanced proficiency in Python and SQL
• Experience working with large-scale customer and transactional datasets
• Ability to communicate insights and recommendations to both technical and business stakeholders
• Experience supporting growth, marketing, customer success, or product organizations is highly desirable

Preferred Experience

• Experience in SaaS, subscription-based businesses, marketplaces, fintech, consumer technology, or digital products
• Familiarity with machine learning frameworks such as Scikit-Learn, XGBoost, PyTorch, or TensorFlow
• Experience with cloud platforms such as AWS, GCP, Azure, or Databricks
• Knowledge of customer journey analytics, attribution modeling, and marketing measurement frameworks

What You’ll Impact

• Customer Retention & Churn Reduction
• Customer Lifetime Value (CLV) Optimization
• Expansion & Upsell Opportunities
• Marketing Performance & Campaign Effectiveness
• Customer Segmentation & Personalization
• Growth Strategy & Revenue Acceleration

To Apply for this Job Click Here

To Apply for this Job Click Here

Founding Data Scientist
NYC (5 Days Onsite – Midtown)
Up to $240K Basic Salary

We’re partnered with an early-stage company operating at the intersection of data, trading, and live events, looking to hire a Founding Data Scientist to help build and scale their core pricing and bidding systems.

This is an opportunity to join a small, high-caliber team where your work will directly influence pricing decisions, inventory strategy, and revenue generation.

What you’ll be working on:
* Pricing and inventory models in a real-time marketplace
* Bidding and trading algorithms
* Machine learning systems used in production
* Model evaluation and performance optimization
* Scaling core data science capabilities from the ground up

What they’re looking for:
* Strong background in machine learning and data science
* Experience building and deploying models into production
* Advanced Python and SQL skills
* Experience working in fast-paced, high-growth environments
* Someone who enjoys solving complex commercial problems

This is a rare opportunity to join at an early stage and help shape both the technical direction and future growth of the business.

Apply below or reach out directly for a confidential conversation.

To Apply for this Job Click Here

To Apply for this Job Click Here

Senior / Tech Lead Product DS

This is a standout opportunity to join a fast growing, AI first scale up where data science directly shapes product decisions. You will work on text driven, AI native products used by high profile global businesses, with real ownership and visibility.

The Company
They are a B2B SaaS business building AI powered products centred on language and user interaction. Founded by researchers and now valued at over $1bn, they operate in a true scale up environment with strong investment in data and analytics.

The Role
You will sit in a central text analysis team working across the business.
Key responsibilities include:
* Analysing large scale, unstructured text and interaction data to understand user behaviour.
* Evaluating AI features, including prompts and model outputs, and defining what good looks like.
* Applying NLP, semantic analysis, classification and regression techniques to drive product insight.
* Partnering with Product and Engineering to influence the roadmap with clear, evidence led recommendations.
* Owning analysis end to end, from problem definition to measurable impact.

Your Skills & Experience
* Strong Python and SQL skills in a product focused data science or analytics role.
* Hands on experience with NLP, semantic analysis, or large scale text data.
* Experience working on AI or ML driven products in a B2B SaaS or scale up environment.
* A pragmatic, impact focused mindset with confidence owning problems end to end.

To Apply for this Job Click Here

To Apply for this Job Click Here

Data Scientist
£45,000-£50,000
Merseyside (Hybrid – 3x Days a Week in Office)

Looking for a Data Science role where your models will actually make it into production? This is an opportunity to join a major UK retail business at a pivotal stage in its Data Science and AI transformation. With a new loyalty programme launching and significant investment into customer analytics, the business is building a scalable Data Science capability focused on real commercial impact

THE COMPANY

This established UK retail brand is investing heavily across Data Science, analytics, and AI as part of a wider business transformation. The organisation is moving away from ad-hoc analytics and building a modern Data Science function capable of supporting customer personalisation, forecasting, and smarter commercial decision-making at scale. The culture is collaborative, pragmatic, and delivery-focused, with a strong emphasis on getting models into production and creating measurable business value.

THE ROLE

You’ll join a growing Data Science team, working closely with the Lead Data Scientist alongside analytics, engineering, and commercial stakeholders across the business. This is a hands-on mid-level Data Scientist role focused on developing and deploying customer-focused machine learning models.

Projects include:

• Customer segmentation
• Customer Lifetime Value (CLTV) modelling
• Demand forecasting
• Propensity modelling
• Targeted promotions and campaign optimisation
• Data Science initiatives linked to a major new loyalty programme

The team are still early in their Data Science journey, making this an excellent opportunity for someone who enjoys building scalable solutions and helping shape best practices.

YOUR SKILLS & EXPERIENCE

The business are open to strong Advanced Analytics candidates looking to transition further into Data Science

• Strong Python experience
• Experience building predictive or customer-focused models
• A practical and commercially minded approach to Data Science

Nice to have:

• Cloud exposure (GCP or Azure)
• Experience with Vertex AI or Azure ML

THE BENEFITS

• Up to £50,000

HOW TO APPLY

Please register your interest by sending your CV to Adam Osborne at Harnham via the Apply link on this page.

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