Senior Data Scientist

Who we are

Active is Built to Accelerate—a category-defining Agentic Intelligence Native Services (AINS) company that equips the teams closest to the work, accelerates business outcomes and builds advantage that compounds. We’ve been named one of the 2026 Inc. 5000’s Top 40 fastest-growing companies in AI & Data and 723 overall in the US.

Expert humans lead. Powerful agents extend what we can accomplish. We scale for velocity, not vanity—and that starts with our people. We expect exceptional judgment, uncompromised excellence and uncommon speed. Think independently. Challenge assumptions. Act decisively. Own the result, not just your assignment. Work without ego, and never confuse activity with impact.

In return, you get meaningful ownership, a voice that can change the direction, direct access to proven leaders and the freedom to build—not simply execute someone else’s instructions. We put decision-making power close to the work and back it with context, trust and clear accountability. Your scope can expand as fast as you demonstrate the ability to carry it; your trajectory is driven by contribution, not tenure or organizational politics.

High-potential talent is welcome. Bring intellectual horsepower, relentless curiosity, pride in your craft and the ambition to take on work bigger than your current title. You do not need to arrive with every answer. You do need to learn fast, seek feedback, honor commitments and make the people around you better. Our agentic teammates amplify that capability; they do not replace your judgment or excuse a lower standard.

This is not a place to coast on a résumé, protect a title or rest and vest. It is a place to do consequential work, earn extraordinary responsibility and grow alongside people who expect as much of themselves as they do of you.

Human-led. AI-powered. Precision-built.

The bar is high. There is no ceiling.

Who you are

As a Senior Data Scientist at Active, you own the intelligence layer of a client engagement: how the system reasons, how we know it is right, and how we prove the result. You work inside the client’s data alongside engineers and consultants, and you settle the questions that decide whether an agentic workflow can be trusted in production. Which tasks need a model and which need a rule? How good is good enough for this decision? What should go to a person, and how will we know if quality slips next month?

Your analysis decides what ships. You build the models and evaluation systems yourself, define the measures the outcome will be judged by, and tell an executive plainly when the data cannot support the claim they want to make. You can explain a confidence interval to an operations lead without losing either the lead or the interval. The field is new enough that the methods you develop for evaluating agents in production will become how Active does it, and you will apply them across healthcare, financial services and marketing instead of inside one product.

We are looking for someone to do the following:

• Embed with client teams and work directly in their data: find it, profile it, assess its quality and lineage, and say plainly what it can and cannot support
• Frame the business outcome as a measurable problem, establish the baseline and design the measurement, using holdouts and experiments where the setting allows
• Decide the method for each task in a workflow (LLM reasoning, classical machine learning, statistical models or rules) and justify the choice on accuracy, cost, latency and risk
• Build evaluation frameworks for agentic systems, including reference datasets from real client cases, automated graders, calibrated human review and regression suites for model, prompt and tool changes
• Develop and deploy models where they are the right tool, such as scoring, forecasting, classification, anomaly and signal detection, retrieval and ranking
• Design risk-tiered review: the confidence thresholds and routing logic that decide which outputs proceed and which go to a person
• Test for bias and uneven performance across the populations a workflow touches, and treat what you find as a design constraint
• Monitor quality, drift, exceptions and cost in production, and define the triggers for reassessment when models or conditions change
• Partner with engineers to put your work into production using sound MLOps practice
• Quantify the result against the baseline and report it with its boundaries intact, including the limits of attribution
• Explain methods, results and uncertainty to client operators and executives in language they can act on
• Contribute evaluation harnesses, measurement templates and model patterns to Active’s shared foundation, and mentor the data scientists and engineers on your team

What you will need to be successful

• Bachelor’s degree in a quantitative field or equivalent experience, and 5+ years of applied data science or machine learning work with systems you built running in production
• Strong programming skills in Python and SQL
• Depth in statistics, experimentation and causal inference, and the judgment to know which method a question deserves
• Hands-on experience building and evaluating LLM applications
• Ability to present complex analysis to technical and non-technical audiences, leading with the decision
• Experience working directly with clients or business stakeholders
• Willingness to travel to client sites as engagements require

Additional preferred qualifications

• Advanced degree (master’s or PhD) in statistics, computer science, mathematics or another quantitative field
• Experience with marketing measurement, attribution or customer journey analytics
• Experience with healthcare or life sciences data, including FHIR, claims or clinical data
• Experience with MLOps tooling, cloud machine learning platforms and model monitoring in production
• Experience with responsible AI practice, including fairness assessment and model documentation

Closing

• Not every strong candidate will match every line above. If the work described here is the work you want to do, apply and tell us what you would bring.
• Active Digital is committed to a diverse and inclusive workplace. Active Digital is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
• If you need a reasonable accommodation at any point in the application or interview process, let us know and we will work with you.