Data Scientist

Data Scientist

What you will be doing:

This position will have responsibility for conceptualizing, designing, implementing, and validating new machine learning algorithms to enhance our Clinical Decision Support Platform. This position will be a member of a multi-disciplinary team comprised of engineers and clinicians. Apply knowledge of statistics, programming, data modeling, and other data science techniques to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement. This individual will be responsible for supporting analyses alongside a Sr./Principal Data Scientist and Product Directors/Senior Directors. This individual will be expected to execute complex analytic protocols under the guidance of these senior team leaders and be able and willing to gain proficiency with new methodologies over time. Deploy knowledge of healthcare datasets, including electronic health records, administrative billing, post-adjudicated claims, purchase order, and invoice datasets.

Key Responsibilities

Responsibility #1– 40%

Algorithm Development and Implementation

• Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data
• Produce innovative solutions driven by exploratory data analysis from complex and highly dimensional datasets
• Work with developers and product engineers to translate prototypes into new products, services, and features, and provide guidelines for large-scale implementation

Responsibility #2 – 25%

Data Strategy and Design

• Participate in data exploration and conceptual design for strategic initiatives
• Apply knowledge of statistics, machine learning, artificial intelligence, programming, data modeling and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement
• Generate and test hypotheses and analyze and interpret the results of product experiments

Responsibility #3 – 15%

Requirements Analysis

• Analyze business requirements, procedures, and problems, design and develop solutions for production
• Develop features and stories based on requirements to feed product backlogs

Responsibility #4 – 10%

Knowledge Sharing

• Provide data science practice advice, demonstrations and presentations to colleagues, clients, and management. Conduct research, as needed
• Provide mentoring and training