What you’ll do:
- Build strong HR Data Science Competency: Develop strategy, build roadmap, and implement future state of retention in HR Data Science. Maintain external view on the state of the art, key trends, and best practices
- Prioritize and lead existing high profile Data Science projects: Proactively identify, prioritize, and rally organization around additional Data Science opportunities based on business strategy.
- Use a combination and quantitative (science) and qualitative (art) methodologies to prioritize ideas
- Provide Advanced Analytics team leadership and mentoring across People Analytics & Operations.
- Conceptually mapping cause and effect relationships to statistical models to develop a robust understanding of business drivers
- Stay on top of fast moving AI/ML models and technologies; understand and follow disruptive data science solutions
- Use a combination and quantitative (science) and qualitative (art) methodologies to prioritize ideas
- Work with engineering and product teams to launch MVPs so we can learn and iterate quickly
What you’ll need:
- Master’s Degree or PhD in a quantitative field (math, computer science, engineering, etc.) required
- 4+ years in Data Science
- 1+ year of management experience preferred
- Demonstrated ability to translate quantitative analysis into actionable business strategies
- Working experience in some of the following data science domains:
- Machine Learning and Predictive modeling
- Text mining and Natural Language Processing
- Recommendation systems
- Data analytics with multi-dimensional data
- Connections to the recommendations and / or information retrieval academic community
- Ability to implement the latest ML research to improve our current algorithms
- Experience and proficiency with various programming languages (e.g., Python), machine learning tools (e.g., scikit-learn, spacy, nltk), deep learning (e.g., pytorch, tensorflow), statistical packages (e.g., Scipy), SQL/relational databases (e.g., Oracle) and NoSQL databases (e.g., MongoDB, graph database), distributed machine learning (spark), Linux and shell scripting
- Experience with cloud computing services such as AWS or Azure ML
- Ability to work collaboratively across product, data science and technical stakeholders
- Experience managing and mentoring data scientists on a wide variety of projects
- Ability to work in a culture that thrives on feedback and seeks opportunities to stretch outside comfort zone
- Experience in People Analytics preferred