Senior Data Scientist

Summary

Join Mercury's Data Science team and leverage your analytical skills to drive product development and adoption. You will partner with cross-functional teams, derive data insights, and translate them into actionable recommendations. Responsibilities include defining key metrics, educating teams on data usage, and employing various analytical techniques. You will collaborate with other data scientists and engineers to build and improve data pipelines. The role requires influencing various teams to implement data-driven recommendations. Mercury offers a competitive salary and benefits package.

Requirements

• Have 5+ years of experience working with and analyzing large datasets to solve problems and drive impact
• Have fluency in SQL, and other statistical programming languages (e.g. Python, R, etc.)
• Have experience building scalable data pipelines and ETL processes with DBT and understand different database structures
• Have the ability to proactively ask questions, turn them into analyses, and make your case to various stakeholders, including senior leadership
• Be super organized and communicative. You will need to prioritize and manage projects to maximize impact, supporting multiple stakeholders with varying quantitative skill levels
• Be familiar with analytical models/analysis used to support product teams

Responsibilities

• Partner with Product stakeholders and other cross-functional teams to identify impactful business questions, conduct deep-dive analysis, translate data insights into actionable recommendations and communicate findings to audiences at all levels to inform data-driven decisions
• Define and analyze metrics that inform tactical decisions and overall strategy for teams that allow us to monitor the health of our products
• Educate teams on how to best use data and define best practices for making decisions on prioritization, experimentation, data models, and more
• Use a variety of exploratory, data visualization, and statistical techniques to uncover actionable insights, including A/B testing, cohort analysis, regression modeling, trend analysis, user segmentation, and machine learning
• Collaborate with other Data Scientists and Data Engineers to build and improve data pipelines, tools, and infrastructure to streamline data collection, processing, and analysis workflows, and ensure the integrity, reliability, and security of data assets
• Influence engineering, design, and business teams to implement data-based recommendations that will improve entrepreneurs’ lives and generate revenue for Mercury

Benefits

• Base salary
• Equity (stock options)
• Benefits