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Senior Machine Learning Engineer

Remote (US) | Up to $190,000 Base + Benefits

A rapidly growing healthcare technology company is hiring multiple Senior Machine Learning Engineer to help build and scale machine learning products that directly improve patient access to clinical research and healthcare innovation.

This is a highly visible opportunity for someone who wants to own machine learning models from development through deployment and monitoring while partnering closely with Product, Engineering, and business stakeholders. The team is investing heavily in data science as a core strategic function and is looking for individuals who enjoy solving complex real-world problems through predictive modeling and statistical rigor.

What You’ll Be Working On

• Building predictive models that influence healthcare decision-making
• Developing patient matching and recommendation systems
• Forecasting enrollment and engagement outcomes
• Designing and evaluating machine learning experiments
• Monitoring and improving production model performance
• Partnering with engineering teams to productionize solutions
• Influencing product strategy through data-driven insights

What We’re Looking For

• 5+ years of ML experience
• Strong Python and SQL skills
• Experience building and deploying predictive models
• Statistical modeling expertise
• Machine learning production experience
• Strong experimentation and analytical thinking skills
• Ability to communicate complex findings to non-technical stakeholders

Preferred Experience

• Healthcare, life sciences, pharma, insurance, or other regulated industries
• Forecasting, Bayesian methods, or advanced statistical modeling
• Experience monitoring and improving production models
• Startup or high-growth environment experience

Why This Role?

• Fully remote opportunity
• Up to $190,000 base salary
• Meaningful healthcare impact
• Strong leadership visibility
• Opportunity to influence product direction
• End-to-end ownership of machine learning initiatives
• Join a business that has proven product-market fit and is investing heavily in growth

If you’re a Machne Learning Engineer who enjoys building models that make it into production and drive measurable business outcomes, we’d love to hear from you.

Apply today or reach out directly for a confidential discussion.

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LEAD DATA SCIENTIST – CREDIT RISK & ADVANCED ANALYTICS

TEMPE, AZ (HYBRID)

$140,000 – $150,000 BASE + ANNUAL BONUS

The Opportunity Join a high-impact Analytics team focused on solving complex business challenges through advanced data science, predictive modeling, and risk analytics.

This is a highly visible leadership role where you’ll partner directly with executives and cross-functional stakeholders to influence key business decisions, improve customer outcomes, and drive measurable financial impact.

You’ll own projects from concept through implementation, applying machine learning, statistical modeling, and business insight to deliver solutions that make a real difference.

What You’ll Do

• Lead analytical initiatives from problem definition through implementation and measurement
• Develop predictive models to support business strategy, financial forecasting, and risk assessment initiatives
• Leverage machine learning techniques such as gradient boosting, random forests, clustering, and segmentation to generate actionable insights
• Identify trends, quantify opportunities, and uncover root causes within large and complex datasets
• Collaborate with senior stakeholders to translate business challenges into analytical solutions
• Present findings and recommendations to leadership through compelling data storytelling and executive presentations
• Guide and mentor less experienced team members on project execution and analytical methodologies
• Build scalable processes and analytical frameworks that improve business performance over time

What We’re Looking For

• 8+ years of experience in data science, quantitative analytics, predictive modeling, or risk analytics
• Experience applying statistical and machine learning techniques to real-world business problems
• Advanced Python and SQL skills with experience working across large, complex datasets
• Strong understanding of predictive modeling, segmentation, experimentation, and statistical analysis
• Proven track record of influencing business decisions through data-driven recommendations
• Excellent communication skills with the ability to explain complex concepts to executive audiences
• Experience leading initiatives independently with minimal direction
• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Economics, Engineering, or a related discipline

Nice to Have

• Master’s degree in a quantitative discipline
• Experience within financial services, consumer lending, real estate, healthcare, or other regulated industries
• Background in risk management, portfolio analytics, or credit-related modeling
• Exposure to model validation, governance, audit, or regulatory review processes
• Knowledge of cloud-based data environments including AWS and Snowflake
• Experience utilizing bureau data, scorecards, or advanced forecasting methodologies

Why This Role

• High-visibility role with regular interaction with executive leadership
• Opportunity to drive business outcomes through production-ready analytics and machine learning
• Strong autonomy and ownership over projects and strategy
• Work on initiatives with measurable multi-million-dollar business impact
• Mentor and influence without direct people-management responsibilities
• Collaborative, supportive culture that values innovation, curiosity, and continuous improvement
• Opportunity to see your models implemented and your work recognized across the organization

If you’re a data science leader who enjoys solving complex business problems, influencing executive decisions, and building predictive models that drive real-world results, we’d love to connect.

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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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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

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

Senior Data Scientist, Causal Inference & Experimentation
London | Up to £124,000 + Bonus

This is an opportunity to join a newly formed Data Science team focused on understanding what truly drives customer value and commercial performance. The role sits at the intersection of Data Science, Econometrics, and Experimentation, with a strong emphasis on explaining why behavioural changes happen rather than simply predicting outcomes.

The Company
They are a global technology and entertainment business investing heavily in advanced analytics to better understand customer behaviour and commercial performance. As part of a newly established function, they are building a specialist team focused on measuring the impact of product and commercial initiatives. The work combines Data Science, Economics, and Experimentation, with a strong emphasis on influencing real-world decisions.

The Role

• Apply causal inference techniques to measure the true impact of product and commercial initiatives
• Design and analyse experiments and A/B tests to drive decision-making
• Conduct cannibalisation, value decomposition, and counterfactual analysis
• Develop simulation and offline evaluation frameworks
• Assess models and experiments developed by other teams
• Translate complex findings into clear recommendations for technical and commercial stakeholders

Your Skills & Experience

• Strong background in Data Science, Econometrics, Economics, Statistics, Behavioural Science, or a related quantitative discipline
• Deep understanding of causal reasoning, experimentation, and statistical inference
• Experience with A/B testing, incrementality measurement, treatment effects, or causal modelling
• Strong Python and SQL skills
• Excellent communication skills with the ability to influence business decisions through data
• Master’s degree or PhD in Economics, Econometrics, Statistics, Mathematics, or a similar quantitative field strongly preferred

What They Offer

• Salary up to £124,000 plus bonus
• Opportunity to help shape a brand-new strategic Data Science function
• High-impact work influencing product and commercial decisions
• Strong career progression and development opportunities
• Flexible working and competitive benefits

How to Apply
If you have a strong background in causal inference, experimentation, and quantitative research, apply today to learn more about this opportunity.

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