The Bill & Melinda Gates Foundation is seeking a Data Scientist to join its People Analytics team in Human Resources. The Data Scientist, People Analytics will design and implement analytics-driven solutions in and outside of the function for the foundation’s most pressing human capital priorities. Focus areas include diversity, equity & inclusion (DEI), organizational and team effectiveness analyses (e.g., manager effectiveness), talent analytics (e.g., hiring, career movement, retention and talent diversity impacts), organizational network analyses and predictive modeling.
The people data scientist role is responsible for distilling and delivering the output of multivariate cross-purpose analyses into actionable insights that enable the foundation to improve its processes and decision-making strategies. Key to success in this role is the ability serve as a strategic partner and consultant to leadership within HR, as well as with cross-foundation senior & executive leadership.
- Design and implement data science research projects that utilize advanced statistical methods, such as regression analysis and machine learning, to address existing talent and program issues, such as attrition, performance, and career progression.
- Ability to design, implement and analyze survey data, including comfort with taking action from the data (including ownership of foundation’s enterprise survey platform and annual employee survey and mid-year manager effectiveness pulse survey).
- Draft technical documents and white papers summarizing data science research projects, including shorter executive summaries for presentation to senior & executive leadership.
- Distill and deliver complex analytics that translate into insights that helps foundation leaders make strategic decisions.
- Provide end-to-end research, program evaluation and strategic support for data-driven changes to programs, policies or initiatives.
People Analytics Background
- At least one year working within the field of people analytics.
Statistical Acumen & Applied Approaches to HR
- Familiarity with descriptive and inferential statistics (e.g., t-test, chi-square, correlation, multi-variate regression, decision trees) to understand usage behaviors, and generate and test hypotheses.
- A demonstrated ability to apply and integrate basic descriptive, as well as more advanced predictive analyses and reporting, to develop strategic and operational insights for HR and organization-wide decision-making (e.g., DEI, organizational and team effectiveness, and talent analytics).
Data Preparation and Data Set Creation
- Comfort working with complex business problems and issues using structured and unstructured data from both internal and external sources.
Experimental Design and Methodology
- Experience designing and analyzing A/B/n experiments, using appropriate statistical techniques to mitigate bias and interpret statistical significance.
- Key to this role is the ability to identify and interpret trends and patterns in datasets to locate influence points, as well as the ability to construct forecasts, recommendations and strategic/tactical plans based on business data and subject area expertise.
Survey Expertise & System Administration
- Support enterprise survey platform, design and deploy surveys, consult with users and report and interpret results.
- This role is accountable for the foundation’s enterprise survey platform, Ultimate Perception, and all annual surveys, survey reporting and analysis, and action planning.
Storytelling with Data
- Excellent verbal and written communication skills with experience distilling and presenting complex data analyses to large and small, technical and non-technical, audiences.
- Provide consultation to stakeholders within and outside of HR, and leading cross-functional teams to address business issues with data-driven written reports, summaries and dashboards.
Required Tool Experience
- Proficiency in a variety of analytical platforms, software languages and statistical tools
- Microsoft Office suite of products
- Data warehouse and management tools (Azure, SQL, AWS, Redshift),
- Data visualization tools (Power BI, Tableau),
- Data preparation and manipulation tools (Alteryx, Python, Databricks),
- Enterprise survey platform administration and utilization (Ultimate Perception, Culture Amp, Glint),
- Multivariate statistical platforms and languages (R, SAS, Stata, SPSS).