Data Scientists 2

Position Overview

The Data Scientist 2 uses mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action.

Key Responsibilities

• Use techniques from supervised and unsupervised machine learning, statistical analysis, or predictive modeling to deliver business insights to prospects and customers.
• Work directly with customers to educate them on moving beyond BI and to train their internal resources in executing advanced forms of analytics.
• Create reusable implementations of statistical tests and models using the available technologies in the ecosystem.
• Collaborate with the academic and business communities to develop new techniques and contribute to research in advanced analytics on large databases.
• Generate new product requirements for the engineering group to enhance the analytics capabilities of the database.
• Assist in customer engagement management, requirements definition, project scoping, timeline management, and results documentation to ensure professional relationship management.
• Use machine learning techniques to assess outcomes of interventions, clinical programs, or marketing campaigns.
• Build “smart” systems that learn from health intervention outcomes over time.

Required Qualifications

• Master's Degree in Math, Computer Science, Analytics, Quantitative Social Sciences, or a related analytical field.
• 2 years of technical experience.
• Experience working with and analyzing various types of data using R, Python, or similar software.
• Proven experience in using mathematics, statistics, modeling, business analysis, and technology to transform large volumes of complex data into advanced analytic solutions.
• Experience using machine learning techniques such as neural networks, random forest, and gradient boosting.
• Naturally curious and comfortable with ambiguity.
• Demonstrated strategic and analytical thinking.
• Clear and concise oral and written communication skills, with the ability to translate complex methodologies and analytical results into higher-level business insights.
• Strong interpersonal and consulting skills.

Preferred Qualifications

• PhD Degree in Math, Computer Science, Analytics, Quantitative Social Sciences, or a related field.
• 3 years of technical experience.
• Experience in a Big Data environment, specifically with PySpark, Scala, or Microsoft Azure.
• Prior experience applying machine learning to help a firm reach its objectives.
• Experience working in a health care and/or insurance setting.