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Senior Analytics Engineer

Princeton, NJ, Boston, MA, NYC, NY

RxSense is a leading healthcare technology company delivering innovative solutions for pharmacy benefits and prescription savings. Our enterprise platform brings transparency, flexibility, and efficiency to pharmacy benefit management, helping clients streamline operations and enabling consumers to save on prescriptions. By integrating intelligence across the pharmacy ecosystem, RxSense makes cost-effective healthcare more accessible. Whether for PBMs, pharmacies, or individuals, our solutions help modernize operations, reduce costs, and improve outcomes. 

RxSense also owns and operates SingleCare, a free prescription savings service that offers consumers access to consistently low prices on prescription drugs. Through its partnerships with the country’s largest pharmacies and grocers, including CVS, Walgreens, Walmart, Kroger and Albertsons, SingleCare improves access and adherence to affordable medications and has helped millions of Americans save over $11 billion on their medications. 

RxSense is a great place to work! Our company has earned several prestigious awards, including Fast Company’s Most Innovative Companies, Forbes’ Top Startup Employers, Modern Healthcare's Best Places to Work in Healthcare, and Inc’s Best in Business and Best Workplaces.

Position Summary:
The Data Science team collaborates closely with the company's Finance, Pricing, and Analytics teams to develop algorithms that create a competitive advantage. The Senior Analytics Engineer is a key member of the Data Science team, partnering specifically with Pricing and Marketing to develop marketing and dynamic pricing strategies for our direct-to-consumer business. Leveraging expertise in data modeling, Python, SQL, and DBT data transformation frameworks, the Senior Analytics Engineer will apply software engineering best practices in the production, management, and maintenance of data essential for the company's analysis, research, and advanced machine learning workflows.

Job Responsibilities:

  • Collaborate with business stakeholders, data scientists, and machine learning engineers to identify, understand, and anticipate data needs, including developing formats for capturing KPIs and designing data structures to support strategic decisions and analytical initiatives.
  • Design and implement fact and dimension tables optimized for business analysts, enabling efficient reporting and detailed analysis of key business metrics.
  • Develop and maintain automated production processes for integrating external data sources, including validation and verification to ensure data integrity.
  • Partner with Engineering teams to source data reliably and scalability through automation.
  • Design, build, and maintain efficient data transformation pipelines and final tables, supporting data governance best practices and data integrity standards.
  • Research industry best practices in data pipeline design and implement improvements accordingly.
  • Assist Data Scientists by preparing data sets optimized for feature engineering and modeling efforts.

Qualifications: 

  • Bachelors degree with 4 plus years of related professional experience; or an equivalent combination of education and experience.
  • SQL s
  • Experience with DBT or comparable data transformation frameworks.
  • Proficiency with Python and Airflow.
  • Extensive knowledge of cloud-based big data platforms (Snowflake, BigQuery, Redshift).
  • Experience developing or directly supporting machine learning models.
  • Familiarity with AI prompt engineering methods and leveraging AI technologies in analytical workflows.
  • Familiarity with modern data stack tools, including CI/CD practices, version control (Git), data observability tools (e.g., Monte Carlo, Datafold), and data cataloging/governance platforms.
  • Experience in SQL, Python, or other data transformation framework.
  • Comprehend principles of applied calculus, algebra and advanced statistical theory to solve complex analytical problems.
  • Apply mathematical thinking to drive engineering decisions, validate assumptions, and support business objectives.
  • Utilize statistical techniques including percentiles, hypothesis testing, and p-value interpretation.
  • Understand machine learning fundamentals such as gradient-based optimization and loss function analysis to develop and refine data for predictive models.
  • Define problems, collect data, establish facts and draw valid conclusions.
  • Interpret an extensive variety of technical instructions in mathematical or diagram form and deal with several abstract and concrete variables. The focus is typically on accuracy, efficiency, scalability, and insightfulness in handling and interpreting complex data.

Salary Range: $98,000 - $140,000

RxSense believes that a diverse workforce is a more talented and productive workforce. As such, we are an Equal Opportunity and Affirmative Action employer. Our recruitment process is free from discriminatory hiring practices and all qualified applicants are considered for employment without regard to race, color, religion, sex, gender, sexual orientation, gender identity, ancestry, age, or national origin.  Neither will qualified applicants be discriminated against on the basis of disability or protected veteran status.  We believe in the strength of the collaboration, creativity and sense of community a diverse workforce brings. 

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