Senior Data Scientist

Summary

Join Mercury as a Data Scientist and partner with the Finance team to build robust forecasts and drive data-based decision-making. Leverage advanced analytics and predictive modeling to analyze large datasets, identify trends, and generate insights for product roadmaps and financial planning. Collaborate with cross-functional stakeholders to refine forecasting processes and improve accuracy. Communicate findings to various audiences to inform data-driven decisions. Build a forecasting platform usable across Mercury with various inputs and model types. Educate teams on data usage and best practices for decision-making. Collaborate with other Data Scientists and Data Engineers to improve data pipelines and infrastructure. Influence engineering, design, and business teams to implement data-based recommendations.

Requirements

• Have 5+ years of experience working with and analyzing large datasets to solve problems and drive impact
• Have strong forecasting experience including methodologies such as ARIMA and Prophet to apply to problems such as LTV and CAC
• Able to work independently with Finance
• 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 Finance and 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
• Build a forecasting platform that can be used across Mercury. Can be used with a variety of inputs to forecast (e.g., users, revenue, profit) and model types
• 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 forecasting techniques to better understand our customer base, business economics, and potential growth levers
• 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

• The total rewards package at Mercury includes base salary, equity (stock options), and benefits
• Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry
• New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers
• US employees (any location): $200,700 - 250,900 USD
• Canadian employees (any location): CAD 189,700 - 237,100