Data Scientist
Skills
SvmBatchNumpyFederated LearningMentoringAws LambdaS3EmrAthenaPrompt EngineeringMachine LearningProbabilityCi/CdModel VersioningPandasSqlPythonComplianceMatplotlibNosqlEc2Unstructured DataMedicareCartBaggingBoostingText MiningSemantic EmbeddingsTextractComprehendHealthcare Payment IntegrityClaims ProcessingGraph Neural NetworksReinforcement LearningStatisticsGenaiData-PipelinesRelational Database DesignQuicksightScipyPower BiOop
About the Role
You will play a pivotal role in developing AI-driven healthcare enterprise applications, working with large datasets to uncover opportunities for product and process optimization. You'll bring hands-on experience in data modeling and solution optimization, along with a proven ability to deliver actionable, data-backed insights. You'll partner closely with internal stakeholders and cross-functional teams to drive meaningful results, and you'll need to adapt quickly to shifting business priorities in a fast-paced environment.
Requirements
- 4+ years of hands-on experience in Python with strong proficiency in Pandas, NumPy, SciPy, Matplotlib, and regular expressions
- Advanced SQL querying and optimization for large datasets
- Practical experience training, tuning, and testing ML algorithms (e.g., SVM, CART, Bagging, Boosting) and text mining techniques
- Experience with prompt engineering and leveraging GenAI for classification, data enrichment, and semantic embeddings
- Ability to integrate multiple data sources into scalable pipelines and work with unstructured data (text, images)
- Strong knowledge of Object-Oriented Programming (OOP) and experience creating custom Python packages for serverless applications
- Hands-on experience with AWS services including Lambda, EC2, EMR, S3, Athena, Batch, Textract, and Comprehend
- Solid understanding of probability and statistics
- Ability to experiment and rapidly prototype design frameworks and iterate on AI/ML models
- Ability to evaluate and optimize models by building robust evaluation frameworks and custom metrics
Responsibilities
- Develop a deep understanding of business challenges and translate them into effective analytical solutions
- Analyze complex datasets to uncover trends, patterns, and actionable insights that support strategic initiatives
- Design, build, and maintain data models and reporting systems using classical and modern machine learning and deep learning algorithms
- Evaluate and report on model performance and business impact
- Identify opportunities for product and process improvements using advanced analytics and machine learning techniques
- Ensure accuracy and reliability of data-driven solutions through testing, validation, and continuous optimization
- Stay current with emerging technologies and best practices in AI, machine learning, and healthcare analytics