Data Scientist

Trek Health; San Ramon (CA); On-site; USD 114,000 - 171,000; Full time

Job summary

An innovative company is seeking a Data Scientist to pioneer their data science practice and influence healthcare pricing strategies. In this role, you will leverage advanced analytics, statistical modeling, and machine learning to provide actionable insights for health systems and provider organizations. Your work will directly impact how healthcare entities negotiate costs and manage resources, making a meaningful difference in the industry. With a focus on collaboration and client engagement, you will design scalable data solutions and present your findings in compelling formats. This is an exciting opportunity to drive change in a mission-driven environment.

Qualifications

• 4+ years in data science, analytics, or ML roles, preferably in B2B SaaS or healthcare.
• Experience building and deploying analytical models at scale.

Responsibilities

• Develop predictive and prescriptive models to address client challenges.
• Lead discovery sessions with clients to understand their KPIs and analytical needs.

Skills

Python

R

SQL

Statistical Modeling

Machine Learning

Data Visualization

Education

Bachelor's Degree in Data Science or related field

Master's Degree in Data Science or related field

Tools

Tableau

Looker

Power BI

scikit-learn

TensorFlow

Job description

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At Trek Health, we’re on a mission to pull back the curtain on healthcare pricing. What started as a small team of data wonks and industry veterans has grown into a platform our customers call “the most accurate, value-driven transparency tool on the market.” We’re backed by $16 million from investors who believe deeply in our mission—Madrona Ventures, Lionheart Ventures, Altman Capital, Founder Collective, and founders/C-suite leaders from multiple unicorn startups. If you want to build something that truly moves the needle for hospitals, health systems, and the patients they serve, you belong here.

Role Description

• Job Title: Data Scientist
• Level: Mid-Senior to Senior (Emerging Leader)
• Manage People: No (individual contributor; you’ll drive initiatives and influence cross-functionally)
• Extract Actionable Insights: Leverage advanced analytics, statistical modeling, and machine learning to uncover key trends, anomalies, and opportunities in our payer transparency data.
• Client-Facing Analytics: Partner with health systems and provider organizations to translate raw data into clear, impactful insights that empower better decision-making.
• Scalable Data Solutions: Design and implement reusable data science frameworks, models, and pipelines that form the backbone of our insights engine.

Key Responsibilities

1 - Advanced Analytics & Modeling

• Develop predictive and prescriptive models to address client challenges (e.g., rate negotiation, network optimization)
• Apply statistical methods and ML algorithms to extract key metrics and forecasts

2 - Client Engagement & Insight Delivery

• Lead discovery sessions with clients to understand their KPIs and analytical needs
• Present findings through compelling reports, dashboards, and presentations
• Collaborate with engineering on data quality, scalability, and governance
• Build reusable data science components and maintain thorough documentation

4 - Cross-Functional Collaboration

• Work with product, engineering, and customer success to integrate analytical models into the platform
• Advocate for data-driven features and best practices across teams

5 - Metrics & Impact Tracking

• Define success criteria and measure the impact of your models on client outcomes
• Continuously monitor model performance and recalibrate as needed

30/60/90 Day Plan

30 Days

• Onboard: data architecture, ETL processes, key datasets, and platform tools

• Analyze a high-priority use case; deliver a “quick-win” insight to the team

• Meet with 5–7 clients to surface top analytical needs

60 Days

• Develop and deploy first analytical model; integrate into a client dashboard or report

• Present model outcomes to customers; gather feedback and iterate

• Draft a roadmap for next data science initiatives with prioritized impact

90 Days

• Deliver a second, higher-complexity model with demonstrable client impact

• Establish a standard process for client-facing analytics (templates, playbooks, docs)

• Define metrics to track data science ROI and set up monitoring alerts

Skills & Experience

Must-Haves

• 4+ years in data science, analytics, or ML roles, preferably in B2B SaaS or healthcare

• Proficiency in Python/R, SQL, and statistical/ML libraries (scikit-learn, TensorFlow, etc.)

• Experience building and deploying analytical models at scale

• Strong data visualization and storytelling skills (Tableau, Looker, Power BI, etc.)

Superpower

• You transform complex datasets into clear, actionable insights that drive decisions

• Healthcare domain expertise can be balanced by exceptional analytical and technical skills

Nice-to-Haves

• Familiarity with payer transparency or claims data

• Experience with big data technologies (Spark, Hadoop)

• Published work or contributions to open-source data science projects

Ideal Attributes

• Roll-Up-Your-Sleeves Mentality: You dive into raw data and aren’t afraid of complex pipelines.
• Client Obsessed: You tailor analyses to each customer’s context and goals.
• Collaborative Thinker: You partner cross-functionally to operationalize insights.
• Fast Learner: You quickly absorb new data domains and statistical techniques.
• Outcome Driven: You focus relentlessly on the metrics that matter to clients and the business.

Demonstrated Success

• Delivered a predictive model that drove a measurable uplift in revenue or cost savings.

• Built client-facing dashboards adopted as core decision-support tools.

• Personal data projects or publications that showcase your passion and expertise.

Why You’ll Love This Role

• Ownership: Pioneer our data science practice and shape how insights power our platform.

• Impact: Your analyses will directly influence how health systems negotiate and manage costs.

• Team: Join a scrappy, mission-driven crew that values data-driven decision making.

Positives

• Autonomy to experiment with advanced analytics and ML.

• Regular client interaction and executive visibility.

• Early-stage environment: you’ll build both models and processes from the ground up.

• Ambiguity: data structures and client needs will evolve rapidly; adaptability is key.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

• Industries

  Hospitals and Health Care

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