Data Scientist

Data Scientist

Location: Remote (This position is based in Hartford, Connecticut. UST will provide relocation assistance)

Description: UST is looking for talented Data Scientists who have experience building data-based solutions powered by the advancement of Machine Learning algorithms and Deep Learning networks. As a Data Scientist (Stars Business Intelligence, Medicare) you will play a critical role in developing analytical capabilities to improve and optimize member experience.

Responsibilities:

As a Data Scientist you:

Should have the ability to communicate data insights to all organizational levels, concluding, defining recommended actions, and reporting results across stakeholders.

Should work on integrating data from different data sources.

Should be working on pre-processing large datasets to build machine learning models, automating, deploying, and maintaining them into production.

Should be able to understand how the deployed models run correctly.

Should develop, test, and deploy data structures using Entity-Relationship Diagramming, and data modeling tools.

Requirements:

1+ years of hands-on experience on Flask and Rest-API, model deployment.

3+ years of hands-on experience with Python, MySQL, and SAS (SAS Enterprise), R, Tableau, SPSS, STATA.

5+ years of experience in data science specialization, including statistical data analysis and/or machine learning in an enterprise-scale environment.

Deep understanding of common database technologies, such as SQL Database/Server, SQL Data Warehouse, Oracle, DB2, Netezza, MySQL, and other data sources, such as Azure Data Lake Storage and Azure Blob Storage.

Experience working with distributed computing tools (Hadoop, Hive, Spark, etc.)

Experience with Cloud Platforms using GCP/Azure/AWS.

Experience with Linux and experience with NLP.

Healthcare Experience is a huge plus.

Expert in Docker, CI/CD deployment, writing YMAL files to implement code and functions as service.

Hands-on experience with real-time streaming processing as well as high volume batch processing, and skilled in Advanced SQL, Amazon S3, Apache Kafka, Data-Lakes, etc.

Experience with Tableau is a plus.

Experience with large scale data mining tools such as Spark

Advanced understanding of best practices for structuring and organizing Data Lake file systems for large volumes of data.

Experience with ML models automation and deployment to production.

Experience performing advanced data pipelines, data structure and modeling, data processing, data extraction, joining, manipulation cleaning, analysis, and presentation for medium to large datasets.

Experience developing models for forecasting, classification, clustering, regression analysis, recommendations, variable selections, and natural language processing.

Experience with scientific computing and analysis packages such as NumPy, Pandas, Scikit-Learn, SciPy, and ggplot2.

Experience with Deep Learning frameworks like PyTorch, TensorFlow, and Keras.

Experience with automated feature engineering/feature extraction and reduction. Experience with data visualization libraries such as Matplotlib, Seaborn Pyplot, ggplot2.

Strong grasp of experimental design, A/B testing, and advanced statistical analysis

Experience with Git, GitHub, and Linux administration.

Experience leading end-to-end data science project implementation including training, testing, and deploying machine learning models in production environments.