Senior Data Scientist - Finance

Senior Data Scientist - Finance

In the 1950s, Norman Borlaug embarked on an effort to breed a new type of wheat that was disease-resistant and had higher yields. In the outskirts of Mexico City, he combined his background of agricultural research and theoretical knowledge with careful experimentation and diligent data collection to run over 6,000 experiments - and he was ultimately successful, kicking off the "Green Revolution" that increased global crop yields by an estimated 44% and earned him a Nobel Prize.

We are looking for a Data Scientist to partner with our Finance team to develop robust forecasts and drive data-based decision-making. In this role, you will leverage advanced analytics and predictive modeling techniques to analyze large data sets, identify trends, and generate insights that inform product roadmaps and financial planning. You will collaborate closely with cross-functional stakeholders in Product to refine forecasting processes, improve accuracy, and help shape company strategy through data-driven recommendations.

Here are some things you'll do on the job :

• 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.

You should :

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.

Our target new hire base salary ranges for this role are the following :

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs.