Data Scientist

State of Wisconsin Investment BoardMadison, WI
8dHybrid

About The Position

About the Team Data Services & Engineering Teams at SWIB supports, implements & develops industry-leading systems and platforms to support SWIB’s diverse and complex set of investment portfolios and strategies. The team at SWIB strives to be a trusted advisor and partner to the business that is valued as a critical contributor to SWIB’s continued growth and success. We effectively leverage technology to derive the maximum value from it and achieve SWIB’s business goals. We keep technology aligned with SWIB’s future direction and operate SWIB’s technology according to industry standards. Position Overview Enable data-driven decision-making through innovative analytical solutions and models. Convey complex data concepts to technical and non-technical stakeholders. Utilize programming languages such as Python and SQL for data manipulation, analysis, and model development. Apply artificial intelligence and machine learning techniques to enhance data analysis, predictive modeling, and decision-making. Act as a liaison between investment personnel and the supporting infrastructure regarding business process change management (IT, Operations, Legal, HR, Strategic Planning, etc.) Implements data quality frameworks and conducting data validation ensuring accuracy of analysis. Develop and deploy models, utilizing techniques such as regression, classification, and clustering. Create interactive visualizations (e.g. Power BI, Streamlit) to effectively communicate data findings. Deploy data solutions in cloud environments (e.g. Azure, AWS). Utilize data warehousing technologies and platforms (e.g. Snowflake) to support analytics initiatives.

Requirements

  • Bachelor’s degree or advanced degree in finance, business, engineering, computer science, computational economics, math, data science or a related program.
  • 1+ years of experience with data science, data analytics, investment analysis, or similar.
  • Proactively drives data-driven decision-making through innovative analytical solutions and models.
  • Exceptional verbal and written communication skills, adept at conveying complex data concepts to technical and non-technical stakeholders.
  • Proficient in programming languages such as Python, SQL, or R for data manipulation, analysis, and model development.
  • Experience applying artificial intelligence and machine learning techniques to enhance data analysis, predictive modeling, and decision-making.
  • Experience implementing data quality frameworks and conducting data validation ensuring accuracy of analysis.
  • Skilled in developing and deploying machine learning models, utilizing techniques such as regression, classification, and clustering.
  • Knowledge of cloud platforms (e.g. Azure, AWS) for data storage and processing, with experience in deploying data solutions in cloud environments.
  • Experience with data warehousing technologies and platforms (e.g. Snowflake) to support analytics initiatives.
  • Experience deploying reports utilizing automated processes Continuous Integration and Continuous Deployment techniques (CICD).
  • Experience implementing testing tools and data quality metrics/processes to ensure overall data quality of reports that are supported and developed.
  • Superb work ethic, attention to detail, team orientation, collaborative disposition, and commitment to excellence.
  • Interest or experience in investment management, quantitative finance and technology.
  • Ability to follow rigor in creating/updating documentation, maintain process (i.e. JIRA tickets) and following technology and business best practices.

Nice To Haves

  • Progress toward or completion of the CFA designation is preferred

Responsibilities

  • Enable data-driven decision-making through innovative analytical solutions and models.
  • Convey complex data concepts to technical and non-technical stakeholders.
  • Utilize programming languages such as Python and SQL for data manipulation, analysis, and model development.
  • Apply artificial intelligence and machine learning techniques to enhance data analysis, predictive modeling, and decision-making.
  • Act as a liaison between investment personnel and the supporting infrastructure regarding business process change management (IT, Operations, Legal, HR, Strategic Planning, etc.)
  • Implements data quality frameworks and conducting data validation ensuring accuracy of analysis.
  • Develop and deploy models, utilizing techniques such as regression, classification, and clustering.
  • Create interactive visualizations (e.g. Power BI, Streamlit) to effectively communicate data findings.
  • Deploy data solutions in cloud environments (e.g. Azure, AWS).
  • Utilize data warehousing technologies and platforms (e.g. Snowflake) to support analytics initiatives.

Benefits

  • Competitive total cash compensation, based on AON (formerly McLagan) industry benchmarks
  • Comprehensive benefits package
  • Educational and training opportunities
  • Tuition reimbursement
  • Challenging work in a professional environment
  • Hybrid work environment
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