Senior Data Scientist

Summary

Join Smartsheet as a Senior Data Scientist to leverage data analytics and machine learning, driving product development and optimizing user experiences. Partner with cross-functional teams to extract meaningful insights and influence key performance metrics. Conduct experiments and A/B tests to measure product impact and identify areas for improvement. Present analyses and data-driven recommendations to encourage informed decision-making. This role requires a Bachelor's degree and 4+ years of experience (or 6+ years), proficiency in Python or R, SQL, and visualization tools, and a proven ability to communicate effectively. You will work primarily with Marketing and Engineering teams and be part of Smartsheet's Business Intelligence team. The ideal candidate will be curious, possess strong data science and machine learning skills, and have a proven track record of forming effective cross-functional partnerships.

Requirements

• Bachelor's degree and 4+ years of experience (or 6+ years of experience)
• Extensive knowledge and practical experience in several of the following areas: product analytics techniques, machine learning, statistics, experimental design
• Proficient analytical skills for problem solving; can perform descriptive analysis, diagnostic analysis, predictive analysis and prescriptive analysis
• Good programming skills in Python or R
• Proficient in SQL and skilled in visualization tools (ex. Tableau)
• Good track record of forming effective cross-functional partnerships
• Experience using data to meaningfully impact product, strategy and execution
• Experience communicating analysis clearly to others
• Ability to research and learn new technologies, tools, and methodologies
• Ability to thrive in a dynamic environment, find opportunities and execute in both independent and collaborative environments

Responsibilities

• Leverage data analytics and machine learning techniques to inform product development, optimize user experiences, and drive key performance metrics such as user acquisition, engagement, retention, and growth
• Partner with Product, UX and Engineering teams, understand their goals, and execute on opportunities to draw relevant insights and drive tangible impact
• Understand our customer needs and design metrics to analyze how our customers are using product and optimize products and features
• Conduct experiments, causal studies and A/B tests to measure the impact of product changes
• Leverage data to understand product performance and to identify improvement opportunities
• Complete the full analytics lifecycle from understanding the business objective and understanding the data to developing automated reporting and visualizations
• Effectively present analysis to teams and give data-based recommendations to encourage data-driven decisions, assisting in product ideation and feature launch decisions
• Think strategically on how to scale your work
• Identify areas for further investigation
• Drive a data culture within the Product, UX and Engineering teams