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Data Scientist
Gainwell TechnologiesData Scientist at Gainwell focusing on data science initiatives in public sector healthcare analytics. Requires extensive experience in SQL and Python with analytical decision-making responsibilities.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Expertise in data science and advanced analytics, with a strong focus on statistical modeling, machine learning, and deriving actionable insights from complex healthcare datasets. Proficient in SQL and Python, with experience in optimizing analytics solutions for performance and scalability.
Highest-signal resume keywords
10+ Years Experience In Data ScienceExpert Proficiency In SQLAdvanced Proficiency In PythonMachine Learning Techniques ApplicationExperience In Major Cloud Environment
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Statistical ModelingMachine LearningData IngestionFeature EngineeringHypothesis TestingSQL Windowing FunctionsPerformance OptimizationData CleansingModel EvaluationTime Series Analysis
Soft Skills
CollaborationMentoringTechnical Leadership
Tools & Technologies
DatabricksCI/CD PipelinesNLP LibrariesAWSAzureGCP
Industry Keywords
Healthcare DatasetsEnterprise DatasetsData Science PracticesSchema On Read TechniquesUnstructured Data
Tech Stack
Tools & technologiesAWSAzureCloudGoogle Cloud PlatformPythonScalaSQL
About the role
Key responsibilities & impact- Support Gainwell's Medicaid and public sector analytics initiatives by leading advanced data science activities across complex healthcare and enterprise datasets.
- Apply statistical modeling, machine learning, and scalable analytics techniques to generate actionable insights.
- Function independently within a business area while collaborating across multiple teams.
- Influence analytical approaches, mentor junior staff, and contribute to improving data science practices.
- Lead data ingestion, cleansing, transformation, and aggregation efforts for large scale datasets.
- Design and implement advanced feature engineering, statistical estimation, and hypothesis testing techniques.
- Develop, validate, and refine machine learning and statistical models.
- Analyze healthcare and enterprise datasets to surface complex, high impact, actionable insights.
- Drive iterative model development and support continuous integration and deployment of analytics solutions.
- Optimize data science solutions for performance, scalability, and production readiness.
- Collaborate with business stakeholders, data engineers, architects, and analysts to align analytics outputs with business objectives.
- Provide technical leadership and guidance to junior data scientists and analysts.
Requirements
What you’ll need- 10+ years of experience in data science, advanced analytics, or related roles.
- Expert proficiency in SQL, including complex set-based query development for large scale datasets.
- Deep, hands-on experience with SQL windowing functions.
- Strong understanding of database concepts such as indexing, stored procedures, and materialized views.
- Advanced proficiency in Python, including object-oriented design and common machine learning libraries.
- Strong knowledge of statistical methods, including time series analysis, repeated measures, mixed effects models, and hypothesis testing.
- Proven experience applying machine learning techniques, including model evaluation, tuning, and lifecycle management.
- Experience with Dev/Sec/Ops practices and CI/CD pipelines for analytics development and deployment.
- Strong experience in performance optimization for both development and production analytics environments.
- Hands on experience using Databricks for enterprise data science workloads; Scala knowledge is a plus.
- Knowledge of semi structured and unstructured data, schema on read techniques, parsers, and NLP libraries.
- Demonstrated experience deriving insights from healthcare datasets.
- Experience performing data science in a major cloud environment (AWS, Azure, or GCP).
Benefits
Comp & perks- Remote working
- Work life balance
- Shift timing: 1pm to 10pm