Senior Data Scientist - Product

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. 

At Mercury, we’re looking to seed our team with candidates who can use their background in analytics applied with product development to accelerate the adoption of Mercury. In this role, you’ll be responsible for proactively deriving data insights and partnering with engineering, marketing, design, onboarding, and other product business teams to inform how we invest in and build Mercury’s future. You’ll  build a data-informed culture across Mercury so that we can all determine what’s happening, react quickly, and invest intelligently. You will develop various skills as a full-stack Data Scientist working on projects end-to-end and build deep domain expertise in the intersection of Data Science and Product..

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

• 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.

You should:

• Have 7+ years of experience working with product teams on goaling, experimentation, funnels, reporting and finding new opportunities with minimal guidance.

• Have fluency in SQL, and other statistical programming languages (e.g. Python, R, etc.).

• Have the ability to proactively ask questions, turn them into analyses, and make your case to various stakeholders, including senior leadership.

• Have experience crafting data pipelines and dashboards, and understand different database structures.

• Be super organized and communicative. You will need to prioritize and manage projects to maximize impact, supporting multiple stakeholders with varying quantitative skill levels. 

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:

• US employees (any location): $203,100 - 238,900 USD

• Canadian employees (any location): CAD 184,800 - 217,400

Mercury is a financial technology company, not a bank. Banking services provided by Choice Financial Group and Evolve Bank & Trust, Members FDIC.

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