Associate Data Scientists produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Apply knowledge of statistics, data modeling, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries. Use a flexible, analytical approach to design, develop, and evaluate predictive models. Generate and test hypotheses.The Associate Data Scientist proactively seeks to develop their skillsets and provide value-added support within the Customer Experience (CX) Measurement & Analytics team.

• Support large projects, and manage smaller projects in their entirety
• Partner with senior team members to assess customer needs and define business questions. Emerging ability to influence internal customers to take action on analytical insights.
• Communicate results and insights, both verbally and written (including visual graphics), in a clear and concise manner to a non-technical audience.
• Identify and communicate roadblocks.
• Work on multiple concurrent projects and accommodate frequent interruptions and changing priorities.
• Effectively participate in meetings with internal customers and emerging ability to guide discussion and decision making.
• With guidance from senior team members identify, define, and translate business needs/problems into analytical questions.
• With guidance from senior team members, design and execute experiments, models, algorithms, and visualizations.
• Understand data sources and limitations, warehousing systems, and the impact of the data on business decisions.
• Identify, retrieve, and manipulate data from internal and external datasets.
• Apply statistical and computational methodologies to provide actionable insights and identify opportunities that optimize quality, consumer experience, and health care and insurance costs.
• Assist with the development of scalable, efficient, and automated processes for large-scale data analyses and model development, validation, and implementation.
• Reporting & Other
• Contribute to technical reports, white papers, and publications.
• Stay current on new processes and technology in data science and communicate findings to team.
• Support other team members as needed.

Required Qualifications

• 2+ years related work experience Data Scientist or similar role
• Related Bachelor’s degree or additional related equivalent work experience
• Data Science, Applied Mathematics, Computer science (e.g. specialization: Machine learning/Artificial Intelligence /Visualization, databases, and Big Data), Statistics, Epidemiology, Health Services Research, or closely related field with Data Science specialization
• Requires experience with statistical packages –- 1-2 years of R (SAS is acceptable) and experience in SQL.
• Strong analytical and problem-solving skills.
• Willingness and ability to support large projects and manage smaller projects in their entirety
• Ability to partner with senior team members to assess customer needs and define business questions. Emerging ability to influence customers to take action on analytical insights.
• Ability to effectively communicate results and insights, both oral and written (including visual graphics), in a clear and concise manner to a non-technical audience.
• Must have applied experience with advanced statistics, e.g. predictive analytics models.
• Must have experience in analytics visualization.
• Experienced in Excel and PowerPoint.
• Must have strong teamwork and collaborative skills.
• Proven ability to meet and exceed deadlines.
• Strong decision-making ability.

Preferred Skills

• Master’s degree
• Experience in Big Data (e.g., Hadoop)
• Experience with other tools (e.g., Tableau, PowerBI, Clarabridge, and Netezza)
• Business intelligence tool development.
• Other programming experience (e.g., Java, Perl, Python, UNIX/Linux scripting)
• Health care, health insurance, medical, pharmaceutical, or customer experience work experience.
• Experience with analyses around quality, consumer experience, and health care and insurance costs.
• Experience in consumer analytics.
• Experience in business analytics.