Description

The Lead Data Scientist uses mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Lead Data Scientist works on problems of diverse scope and complexity ranging from moderate to substantial.

Responsibilities

The Lead Data Scientist is expected to quickly understand the Group Business operations and data ecosystem and Business context of the data, work closely with GBO Insights Council to establish the key insights needed to understand and  improve our member experience and Net Promoter Score (NPS) from all aspects of engaging with Humana.

Applies advanced knowledge of statistical modeling, exploratory data analysis, business analysis, analytics platforms and Machine Learning to recognize patterns, identify opportunities, develop descriptive and predictive analytics models to generate actionable business insights and predictions to improve member experience, process optimization and achieve overall service and operational cost reduction.

Responsibilities

• The Lead data Scientist is expected to work closely with the Insights Council, is really enthusiastic, confident, assertive and humble in what they bring to the table to really push things to move forward.  Develops and maintains data lakes of structured and unstructured data sets for analysis and reporting.
• Develops scalable, efficient, and automated processes for large scale data analyses and model development, validation, and implementation.
• Responsible to lead projects to deliver “insights” as prioritized by the Insights Council
• Design and execute experiments, models, algorithms, and visualizations to test hypothesis
• Build descriptive, predictive and prescriptive models to help answer critical questions in the business context -  “how do we measure success ?”,  “where and when can we improve ?”,  “why does this matter?”,  “what can we do differently?”,  “how can we provide better insights?”
• To understand all aspects of Group business – Products, membership, enrollment, support, calls, claims etc along with cross functional subject areas like Clinical and Pharmacy to build comprehensive predictive models to predict NPS/member experience based on variability of these dimensions
• Communicate results and insights, both verbally and written (including visual graphics), in a clear and concise manner to a non-technical audience.
• Understand data sources and limitations, warehousing system and the impact of the data on business decisions.
• Work on multiple concurrent projects and accommodate frequent interruptions and changing priorities, exercises independent judgment and decision making and works under minimal supervision
• Advises executives to develop insight-driven functional strategies (often segment specific) on matters of significance
• Stay current on new processes and technology in Data Science and communicate findings to team
• Supervise, coach and develop internal data science and analytics talent
• Present innovative research in national/international conferences and journals

Required Qualifications and Experience

• Bachelor’s degree (with 8+ years of technical experience) or Master’s Degree (with 5+ years of technical experience) in Statistics, Mathematics, Applied mathematics, Computer Science, Data Science, Business Analytics or related discipline
• 2+ years of project, process or people leadership experience, managing team
• 4+ years of experience in Health Insurance industry, with solid understanding of Process and data related to one or more of these subject areas - Membership, Product designs, Calls, Enrollment, Claims, Clinical and Pharmacy
• Ability to quickly comprehend business asks and understand the context and the big picture
• Solid knowledge of current developments and best practices in Data Science, analytics tools and platforms, Industry standards, data and privacy compliance standards
• Experience with Deep Learning models, AI development,  Tensorflow and Machine Learning algorithms, ETL, SQL, SAS, R, Python and visualization tools such as Tableau and QlikSense/Qlikview
• Designing and building algorithms and predictive models using techniques such as linear and logistic regression, support vector machines, ensemble models (random forest, gradient boosted trees), neural networks, and clustering techniques.
• Prior experience working in Bigdata technology and Cloud-based analytics infrastructures, stream analytics, data fabrics etc
• Must be a Leader, driving initiatives from concept to implement with minimal to no supervision
• Innovative, strategic, with great negotiation and communication skills.
• Clear and effective communication of operational strategy, insights, predictions etc both verbally and written (including visual graphics), in a clear and concise manner to a technical and non-technical audience
• Prior experience and interest in coaching and mentoring junior talent to grow next generation of Data Scientists

Preferred Qualifications and Experience

• Masters or Post-graduate studies in Applied Mathematics, Computer science (e.g. specialization: Machine learning/Artificial Intelligence /Visualization, databases, and Big Data), Statistics, Health Services Research, or closely related field with Data Science specialization
• Experience in Health Insurance consumer analytics
• Experience with deploying model pipelines across various technologies, such as Kubernetes or Docker.
• Experience with Natural Language Processing, Keras, and/ or H2O
• Experience working in Agile environments

Primary Location :
United States- Dallas, Chicago, Boston (MA), Overland Park (KS).

Preferred operating time is from 8:00 AM – 5:00 PM CST