Clinical Data Science Manager

Clinical Data Science Manager

CONTEXT & INITIATIVE DESCRIPTION

Eliassen Clinical Solutions is partnering with a Fortune 100 healthcare research company to provide access to groundbreaking medications and treatments for a diverse range of underrepresented populations and we are hiring a Clinical Data Science Manager to work cross functionally on exciting initiatives.

This Data Science Manager will make use of artificial intelligence (AI), machine learning (ML), statistics, and deep learning to create predictive models using retail healthcare data.

This position is a full-time salaried position with Eliassen Clinical Solutions, complete with 401k, healthcare benefits, PTO, and Holiday Pay.

Job Description:

The Clinical Data Science Manager will be assisting in investigating complex business problems through a range of data preparations, modeling, analysis, and/or visualizations techniques, including predictive analysis, business intelligence, pattern recognition, operational effectiveness, and forecasting.

MUST HAVES

• Strong python and SQL programming experience
• 5+ years of relevant consulting or industry experience; ability to thrive in a fast-paced, dynamic, client-facing role
• Strong prioritization and multitasking skills with a track record of meeting deadlines
• Familiarity with cloud-based platforms such as GCP (preferred), Azure, or AWS
• Ability to be creative and analytical in a problem-solving environment
• Knowledge of deep learning models across a range of input modalities. Must have the ability to evaluate the tradeoffs between building, finetuning, or reuse of existing models
• Must be able to quickly prototype a wide range of models/solutions using traditional ML (linear classifiers, GBTs, k-means, etc.), deep learning, or non-model-based solutions (statistical analysis, graph algorithms, etc.).
• Must have knowledge of retail pharmacy and clinical data.
• Strong communication skills, including the ability to explain difficult modeling decisions to technical and nontechnical stakeholders and to create complex data visualizations to support stakeholder understanding
• Strong data management skills, including the ability to write complex SQL queries for data extraction, perform data exploration and cleaning, and perform feature engineering
• Strong ability to translate complex research questions into efficient data science / ML workflows, even when computer resources are limited

TRAVEL & LOCATION

REMOTE

START & TERM

Immediate

CONSULTING RATE

Competitive.