Summary of Major Responsibilities
The Data Scientist performs data analysis to extract knowledge or insight from structured or unstructured data. This position will apply advanced statistical algorithms for analysis of large-scale, complex datasets. This position will keep up to date with cutting-edge techniques in programming, machine learning, big data, and healthcare modeling and will seek ways to advance the organization's capabilities in analytics.
This position will also be responsible for developing and automating data pipelines, cleaning, and preparing data, and debugging data issues for the analytics team. This position will monitor production data sources, resolve issues, improve system performance, and serve as a technical resource for analysts and other users of data within the analytics and finance teams. Essential Duties and Responsibilities
- Apply machine learning, deep learning, and artificial intelligence techniques.
- Use advanced analytics methods to extract value from business data.
- Perform large-scale experimentation and build data-driven models to answer business questions.
- Create hypotheses and experiments to identify hidden relationships and construct new analytics methods.
- Develop and implement Markov decision process models and healthcare economic models.
- Articulate a vision and roadmap for the utilization of data as a valued corporate asset.
- Visualize information and develop reports on results of data analysis.
- Influence product teams through presentation of data-based recommendations.
- Spread best practices to analytics and product teams.
- Implement new tools to make data analysis more efficient.
- Ability to work with minimal supervision.
- Ability to work in a highly collaborative environment.
- Ability to communicate complex results to technical and non-technical audiences.
- Excellent verbal and written communication skills.
- Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork.
- Support and comply with the company's Quality Management System policies and procedures.
- Regular and reliable attendance.
- Ability to lift up to 10 pounds for approximately 5% of a typical working day.
- Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 80% of a typical working day.
- Ability and means to travel between Madison locations.
- Ability to travel 5% of working time away from work location, may include overnight/weekend travel.
- Bachelor's degree in computer science, data science, information technology, or related field.
- 3+ years of experience working with large datasets for drawing business insights.
- 1+ years of experience in a data science role.
- Professional working knowledge of machine learning; including solving complex business problems, predictive modeling, leveraging both structured and unstructured data sources, relational databases, and SQL.
- Professional working knowledge of statistics and modeling techniques.
- Fluent in Python or R programming.
- Demonstrated ability to learn new technologies.
- Proficient in Microsoft Office.
- Demonstrated ability to perform the Essential Duties of the position with or without accommodation.
- Authorization to work in the United States without sponsorship.
- Master's or PHD degree in science, technology, engineering, mathematics, or related field.
- Experience with developing code to perform ETL actions, free-form text searches, pattern matching, data mining, and data blending.
- Professional working knowledge of distributed computing and big data technologies, such as Spark or related technologies.
- Professional working knowledge of statistical methodologies and tools (R, SAS, SPSS, etc.), mathematical optimization, control theory, and time-series analysis.
- Professional knowledge of data warehouse automation solutions.
We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, creed, disability, gender identity, national origin, protected veteran status, race, religion, sex, sexual orientation, and any other status protected by applicable local, state or federal law. Applicable portions of the Company's affirmative action program are available to any applicant or employee for inspection upon request.