Director of Data Science

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Human Health Project (HHP)’s has a three- pronged foundation: Holistic Peer-to-Peer Information, Education and Support. Our objective is to empower people to manage their own health with improved outcomes and no medical errors. For more information, please visit our website including viewing our Real World Data program page which includes 50 pages of reports on our Migraine and Lupus pilot programs and feedback received from people who reviewed the reports in the section, "What Our Members are Saying" https://humanhealthproject.org/hhp-real-world-data-program/

Job Overview:

As a volunteer Director of Data Science for HHP, you will be responsible for leading a team ensuring best in class methodologies and deliverables across the entire data journey from Descriptive to Predictive analytics. This is a highly visible and critical role that will drive HHP’s strategy for our product offerings and experiences.

Requirements:

• Bachelor’s degree with 10+ years of experience OR Masters Degree with 9+ years of experience OR PhD with 7+ years of experience
• Degree preferably in engineering, economics, statistics, computer science, or related quantitative field.
• Preferred experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field
• Expert level knowledge of applied regression techniques including, but not limited to: Linear, Logistic, Mixed models, Time Series, General Linear Models & Simultaneous Equations. You also have experience in the use of Neural Network models for sales forecasting and GAN models.
• Expertise in statistical data analysis and mathematical methodologies for unsupervised & supervised learning algorithms. Expertise in a wide variety of techniques such as neural nets, deep neural nets, boosted trees, support vector machines. Algorithm development in graph mining and social network analysis is a plus
• Expert level knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and or working in Snowflake/Databricks
• Conceive and coach the design of end to end scripted analytics solutions using Python, Scala, Java, or R as well as modern analytical systems in Spark + Hadoop/Databricks/Snowflake.
• Demonstration of a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.

Responsibilities:

• Forming teams, organizing analytical processes and workflows, and mentoring/developing the managers who work on your team as well as junior team members.
• Use advanced machine learning techniques for driving highly applied analyses and tools to directly drive revenue and optimize resources.
• Building and leading enterprise teams to develop end-to-end ML/AL solutions and applications at large scale in the Cloud.
• Conceptualize, document and deploy complex analytical plans to take on business problems.
• Lead ongoing and ad-hoc analyses and predictive analytics to provide leadership with actionable insights at tactical and strategic levels.
• Background in healthcare, Pharma, or health payments analytics experience is highly preferred.
• As a Subject Matter Expert (SME) you will be responsible for the structural development, integration, implementation, and use of Data-Sciences systems
• You will partner with IT and technical teams to develop and implement a digital roadmap and to develop reporting and analytics tools, dashboards, and other modes of data presentation.
• You will partner with process development and manufacturing on development of platform analysis systems, platform analytics, technology innovation, and systems implementation as well as to provide statistical analysis support to process development, manufacturing, and Quality teams.
• You will collaborate to develop systems and procedures to enable proactive process monitoring, analysis, and reporting of manufacturing process data.
• You will assess, communicate, and mitigate key technology and data-systems risks in a timely and effective manner.