Description:
As a Data Engineer / Scientist you would be at the forefront of enabling new value based healthcare models and delivering constantly evolving analytics services to the industry. You’ll have an excellent opportunity for professional growth in the fields of healthcare economics, quantitative analytics and related technologies.
- Build complex data transformations and statistical models using Python, SQL, SAS.
- Perform EDA, scenario modeling, forecasting and simulations on large datasets.
- Ingest, transform, clean and augment internal and external data assets. Automate data pipelines to process. patient-level and aggregated public health data.
- Leverage an ever evolving range of cloud services, data science libraries and database platforms, such as AWS (EC2, RDS, S3, Lambda, Redshift, Athena, Glue), Databricks/Spark, PostgreSQL, SparkSQL, Python, Pandas, PySpark, Apache Airflow, and DST.
- Continuously learn by investigating new technologies and mentor other team members.
REQUIREMENTS
- BS or MS in Computer Science or Mathematics from a top university program. Experience with data science concepts, building statistical models deployed on scalable data platforms
- Experience with EDA (exploratory data analysis) using a variety of Python libraries or BI platform tools
- Experience with hands on SQL, writing complex data transformation queries and optimizing for performance on large scale data (Knowledge of Databricks or other Spark environments is preferred)
- Solid understanding of data pipelines, processing parallelization, and ETL concepts. (Familiarity of the following items are optional, but preferred: Concepts used by ETL tools such as DBT and SSIS; Apache AirFlow and other job orchestration tools; Linux command line, shell utilities and Git / GitHub; Docker and environment management)
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- Experience with AWS or other PaaS cloud services (such as AWS S3, RDS, Redshift, EMR, and Lambda) are a plus
- Desire to be an expert in healthcare economics and passionate about making an impact in this field