Über diese Senior Health Data Consultant Stelle bei Gradient AI
Gradient AI · Remote · Remote
This is a remote role.
Gradient AI:
Gradient AI is revolutionizing Group Health and P&C insurance with AI-powered solutions that help insurers predict risk more accurately, improve profitability, and automate underwriting and claims. Our SaaS platform taps into one of the industry’s largest data lakes—tens of millions of policies and claims—to deliver deep, actionable insights. Trusted by leading carriers, MGAs, TPAs, and self-insured employers, Gradient AI has grown rapidly since our founding in 2018. Backed by $56M in Series C funding, we’re scaling fast—and it’s an exciting time to join the team.
About the Role:
We’re looking for a Senior Health Data Consultant to partner closely with our clients and internally to drive adoption and value of Gradient AI’s services within our Group Health products. This is a client-facing, analytics-driven role focused on pricing consultations, AI model adoption, renewal analytics, and risk interpretation—helping clients translate model outputs into clear underwriting and pricing decisions. This role blends technical depth (math, analytics, coding) with consultative client engagement. It is ideal for someone who is highly quantitative, comfortable working directly with AI-driven model outputs, and excited to guide clients through data-driven pricing and underwriting decisions.
How you will make an impact:
- Engage directly with clients to provide advanced analytical support.
- Lead pricing consultations for Group Health SAIL and Renewal products, helping clients interpret risk scores and model outputs.
- Partner with internally with Client Services, Sales, Product, and Data Science to support our clients across new sales and renewals.
- Analyze data using internal tools to evaluate pricing risk and provide recommendations.
- Dive deep into AI-generated outputs to explain what model outputs and risk indicators mean in practical underwriting and pricing strategies.
- Write and execute SQL and Python queries to analyze large datasets and evaluate submission performance.
- Build and refine advanced Excel models to stress-test pricing assumptions and validate model results.
- Clearly communicate complex mathematical and AI concepts to non-technical client stakeholders.
- Help quantify ROI and performance improvements tied to our AI products
Skills needed to succeed:
- 5+ years of experience in a healthcare analytics, population health, healthcare economics, or claims analysis role, with an actuarial perspective.
- Strong quantitative background in Statistics, Mathematics, Economics, Analytics, or a related field.
- Proficiency in Python and SQL required; advanced Excel skills required.
- Ability to interpret complex statistical outputs and clearly communicate insights to non-technical stakeholders.
- Analytical support for health insurance populations (e.g., renewal pricing, retention, trend management, or book-of-business optimization)
- Comfortable engaging directly with clients in a consultative capacity and presenting analytical findings.
- Proven experience building or refining pricing models, running data submissions, and validating model-driven results.
- ASA certification is a plus.
- Exposure to modern data platforms such as Databricks is a plus.
What We Offer:
- A fun, team-oriented startup culture.
- Generous stock options - we all get to own a piece of what we’re building.
- Unlimited vacation days.
- Flexible schedule that supports working from home.
- Full benefits package includes medical, dental, vision, 401k, paid paternal leave, and more.
- Ample opportunities to learn and take on new responsibilities.
We are an equal opportunity employer.
Salary Range: $120,000-160,000 base salary annually.
This role is also eligible for an annual performance bonus, equity grant, and a comprehensive benefits package. In accordance with the Massachusetts Pay Transparency Law, we are providing a good-faith salary range for this position at the time of posting. The actual salary offered will depend on the level at which the candidate is hired, as well as their experience, skills, qualifications, and location. Compensation may grow over time through merit-based increases, promotions, and company-wide adjustments. If your salary expectations fall outside this range, we still encourage you to apply so we can have a conversation.
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