SmithRx is looking to solve the problem of expensive and inefficient Pharmacy Benefit Management (PBM) sector by building a next-generation drug acquisition platform driven by cutting edge technology, innovative cost saving tools, and best-in-class customer service.
Requirements
- Advanced technical proficiency, including deep experience: Leveraging SQL & dbt to query, transform, and validate complex data sets
- Leveraging scripting languages (e.g. Python) and statistical/mathematical software (e.g. R) for advanced statistical modeling
- Collaborating with Data & ML Engineers to architect robust data models and institute world-class data quality guardrails
- Establishing and scaling causal learning frameworks, including designing and executing experiments with statistically significant findings
- Designing, presenting, and influencing people with data visualizations that deliver impactful and actionable insights
- Leveraging SQL & dbt to query, transform, and validate complex data sets
- Proficiency in statistical/mathematical software (e.g. R)
Responsibilities
- Drive Goal-Setting & Decision-Making: Partner with Product, Clinical, CS, and GTM stakeholders to deeply understand their domains and define success states for each through data-driven goal-setting
- Architect Data Foundations: Collaborating closely with Data & ML Engineers, influence the design, development, and maintenance of dimensional data models, ensuring data reliability and accessibility
- Elevate Data Quality Rigor: Champion world-class data governance practices, continuously raising the bar for data & code quality across tech teams
- Amplify Team Performance: Operate as a force multiplier that fosters growth within the team, providing incisive technical mentorship, inspiring intellectual curiosity, and driving clarity amidst ambiguity
- Design key metrics that showcase progress toward our goals and uncover opportunities to deliver product and business improvements to achieve them using advanced statistical methodologies
- Influence decision-making by designing and executing experiments that rigorously evaluate the viability of those opportunities with statistical significance
- Establish and scale causal learning frameworks, including designing and executing experiments with statistically significant findings
Other
- Bachelor’s degree in a quantitative field (e.g. mathematics, statistics)
- 8+ years of hands-on experience influencing product and business decision-making through experimentation and advanced analytics
- A self-starter mentality, proactively identifying novel ways to drive impact, devising creative solutions to complex challenges, and independently delivering on commitments
- Excellent communication and storytelling skills, seamlessly adapting between business and technical audiences
- Proven leadership prowess, including the ability to drive clarity by articulating a compelling vision and bring people along with you
