Data Scientist – Analyst
MedReview Inc.
full-time
Posted on:
Location Type: Remote
Location: Texas • United States
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About the role
- Collaborate with ML engineers and data platform teams to design, implement, and maintain the feature store architecture for both offline (batch) and online (real-time) use cases.
- Identify, define, and engineer high-quality features from various raw data sources (databases, APIs, streaming data) using statistical analysis and domain knowledge.
- Partner with database administrators, clinical experts, data scientists, ML engineers, and business stakeholders to promote feature reuse, define governance standards, track feature lineage, and ensure data consistency across models.
- Build and optimize ingestion and transformation pipelines using distributed data frameworks to populate the feature store, ensuring data accuracy, reliability, and freshness.
- Generate training and testing datasets from the feature store and work with ML engineers to ensure seamless feature serving for model inference in production environments.
- Develop monitoring and alerting frameworks to track feature data quality, integrity, and latency, proactively identifying and resolving issues.
- Document feature definitions, data sources, and usage best practices, and effectively communicate complex technical concepts and insights to technical and non-technical audiences.
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field
- 3+ years of experience in data science, data engineering, or MLOps roles, with a focus on data infrastructure and machine learning workflows.
- 1+ years of experience in a health care industry company or familiarity with health care claims, coding and clinical decision making
- Strong programming skills in Python, R and SQL
- Experience with data processing frameworks (e.g., Spark, Flink, Airflow).
- Hands-on experience with feature store technologies (e.g., Feast, SageMaker Feature Store, Tecton, or custom implementations) is preferred.
- Familiarity with cloud platforms (AWS, Azure, or GCP) and related data services.
- Knowledge of machine learning fundamentals, statistical modeling, and data visualization tools.
- Familiarity with Clickhouse or similar technologies is a plus
- Experience working in an Agile environment
Benefits
- Health insurance
- Flexible work arrangements
- Paid time off
- Professional development opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonRSQLdata processing frameworksSparkFlinkAirflowfeature store technologiesFeastSageMaker Feature Store
Soft Skills
collaborationcommunicationproblem-solvingdocumentationdata governance
Certifications
Bachelor's degreeMaster's degree