Decision Scientist Lead
$173k - $260k • Remote • California - San Francisco
Posted 1d ago
Job Location
California - San Francisco
Tech Stack
Remote Work Policy
Fully remote
Categories
Machine Learning Engineer
About the job
Salesforce is seeking a Decision Scientist Lead to join the Data Solutions team, which drives the company's progress in the 4th Industrial Revolution through trusted data and artificial intelligence. This role will lead the team responsible for developing the data foundation, metrics, and insights for Data 360, informing the path forward to be smarter in every dimension. The Data Solutions team acts as an unbiased partner, providing crucial information for financial forecasting, customer health, adoption insights, and curated data. This is an opportunity to lead a team of high-achieving analysts and engineers, partnering with cross-functional teams to solve complex business problems using data and AI.
Responsibilities
- Serve as a thought leader and trusted advisor to T&P leaders, including the General Manager, COO, Product Owners, and other decision-makers for Data 360.
- Lead a team of analysts, data engineers, and visualization engineers in partnering with cross-functional teams to understand business problems, synthesize data, and apply mathematical/statistical methods.
- Develop hypotheses, test them, and overlay business context to explain outcomes and provide prescriptive recommendations.
- Foster cross-functional collaboration by building strong relationships with key partners across the company.
- Inform the product roadmap development and execution for Data 360 product analytics, including releasing data products and dashboards.
- Establish the team's roadmap, prioritize impactful work, and guide the team in solving ambiguous and complex problems.
- Develop metrics and product insights to drive Salesforce's Data 360 adoption and consumption.
Requirements
- 8+ years of experience as a data scientist or analytics professional with a proven track record of delivering impact through modeling and/or analytics.
- MBA or Master's degree in a quantitative field (computer science, computer engineering, economics, applied math, statistics, engineering).
- Experience working directly with senior executive leadership.
- Proven experience delivering enterprise-scale predictive modeling initiatives and applications.
- Expert written and verbal communication skills, with the ability to work with executives and technologists and influence across all organizational levels.
- Demonstrated ability to think creatively and solve complex problems.
- Proficiency in statistics or machine learning, strong data manipulation, product analytics, and statistical analysis skills.
- Proficiency in Python or R, specifically the PyData stack (Pandas, NumPy, SciPy, Statsmodels, Scikit-learn).
- Mastery of SQL for complex data extraction, feature engineering, and performance tuning in cloud data warehouses.
- Experience leveraging AI tools to enhance workflow.
- Willingness to work across global teams and time zones.