Senior Data Scientist

emendata; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Emendata is seeking a data scientist to turn open-ended questions into practical analytic solutions. You will operationalize research questions, profile data sources, and develop robust models using statistical and machine learning methods.

The role emphasizes clear communication to technical and non-technical audiences and collaboration with clients on policy and program contexts. Ideal candidates have advanced degrees (MS/PhD) and 3+ years of relevant experience, with strong Python, R, and SQL

Qualifications

• Advanced degree in data science, CS, statistics, or related field with 3+ years of experience
• Strong grounding in statistical and ML methods used in practice
• Experience writing code for data analyses in Python, R, or SQL

Responsibilities

• Turn questions from management into analytic frameworks and deliverables
• Profile data sources, build datasets, and craft meaningful features
• Evaluate analytic methods and choose appropriate approaches for the problem
• Develop analyses and models with a disciplined, iterative process
• Design validation, baselines, tests, and sensitivity analyses
• Produce clear reports and presentations for technical and non-technical audiences
• Collaborate with stakeholders to refine approaches and incorporate feedback
• Stay current on analytic methods and contribute to institutional knowledge

Skills

Data science

Machine learning

Python

R

SQL

Education

M.S. or Ph.D. in data science or related quantitative field

3+ years of relevant professional experience

Tools

Python

R

SQL

Job description

About Us:

At Emendata, we help bridge the gap between data and the real world. We partner with organizations that have a social mission and help them tackle their problems using analytics. Our role in these partnerships goes end to end-we handle everything from wrangling the data to analyzing the problem to turning the results into something actionable. We know that this analytics pipeline does not live in a vacuum. Getting to meaningful numbers requires more than just the right methods; it calls for understanding the people, policies, data, and systems involved.

With this approach, our small but fast-growing team is having a big impact taking on challenges in healthcare program integrity - safeguarding programs like Medicare and Medicaid by preventing fraud, waste, and abuse. We are growing our team with people who enjoy figuring out hard problems, want their work to matter, and set a high bar for themselves and their teammates.

About the Role:

We are looking for someone to turn ideas into practical analytic solutions. The ideal candidate can bring structure to an open-ended question, determine what needs to be understood, and thoughtfully chart a clear path forward. They pair a strong analytical foundation with the ability to apply what they know and determine what makes sense for the problem at hand. They maintain momentum from the initial question through the final deliverable and care deeply about producing work that is sound and that others can understand and act on. Just as importantly, they have a track record of seeing this kind of work through successfully in a professional setting.

We are looking for you to:

• Operationalize research questions from management and clients into robust analytic frameworks, research activities, and deliverables with minimal direction
• Explore and profile data sources to understand their structure, quality, and limitations; build reliable datasets and develop meaningful features for analysis and modeling
• Research and evaluate analytic methods, tools, packages, and implementation options, then select the approach best suited to the question, data, intended use, and computing environment
• Develop analyses and models using appropriate statistical, machine learning, and other analytic methods, following a disciplined, iterative process that includes clear planning, documentation, testing, and review
• Design and carry out appropriate validation, using methods such as baseline comparisons, test cases, sensitivity analyses, and record-level review
• Produce clear, well-supported deliverables, such as reports and presentations, that explain the data and methodology, interpret findings, and provide conclusions and recommendations to technical and non-technical audiences
• Collaborate with stakeholders to understand the policy and operational context, refine analytic approaches, and incorporate feedback throughout the development process
• Stay current on relevant analytic methods, tools, and applications; contribute to the development of the company's institutional knowledge

Required Qualifications:

We are looking for you to have the following qualifications:

• Education and Experience : M.S. or Ph.D. in data science, computer science, statistics, applied mathematics, engineering, economics, or a related quantitative field, plus at least 3 years of relevant professional experience; or a bachelor's degree in a related field plus at least 5 years of relevant professional experience
• Technical Expertise : Strong theoretical grounding in statistical and machine learning methods, with professional experience selecting, implementing, and evaluating methods in practice; familiarity with predictive modeling, anomaly detection, graph and network analytics, and natural language processing
• Programming : Experience performing analyses using Python, R, or SQL
• Communication : Ability to write clearly and communicate effectively with technical and non-technical audiences
• Interests : Strong interest in social science research
• Working Style : Capable of working with minimal supervision and a high level of initiative; practical approach to problem-solving; comfortable working both independently and collaboratively on client-facing projects
• Ownership : Demonstrated ability to organize work effectively, communicate progress and challenges, and drive work to completion

Desired Qualifications:

• Consulting Experience : Experience developing and delivering analytic work in a consulting or other client-facing environment
• Technical Expertise : Experience implementing approaches in a professional setting in one or more of the following analytic areas: predictive modeling, anomaly detection, graph and network analytics, or natural language processing
• Domain Expertise : Knowledge of healthcare data, policy, and program integri