Senior Data Scientist - Machine Learning
In the dynamic domain of financial technology, Machine Learning (ML) paves the way for intelligent product evolution, intertwining data-driven insights with user-centric solutions. At Mercury, our mission is to amplify our product intelligence, merging ML expertise with discerning product sensibility.
We are currently seeking a Senior Data Scientist with expertise in Machine Learning, whose skills will be fundamental in building intelligent products that are not only reactive but proactive in fulfilling user needs. In this role, you will spearhead initiatives to harness machine learning to strengthen risk management frameworks and enhance customer experiences.
As part of this role, you will 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. Your work will play an early role in establishing a data-informed culture across Mercury, enabling us to better understand events, react swiftly, and make intelligent investments.
Here are some things you’ll do on the job:
- Engineer, validate, and deploy machine learning models in production, focusing on personalizing user experiences and automating risk assessment processes to ensure our products continually adapt to meet user needs and mitigate potential risks.
- Collaborate closely with product teams to integrate ML insights into our product ecosystem, driving the creation of more intuitive, responsive, and secure banking* solutions.
- Apply ML algorithms for real-time fraud detection, credit risk assessment, market risk prediction, and regulatory compliance monitoring, ensuring a robust risk management framework.
- Partner with engineering, design, and business teams to implement ML-driven recommendations, fostering a culture of data-informed decision-making and continuous product innovation.
- Stay updated on the latest ML technologies and methodologies, iterate on existing models, and explore new avenues to enhance product intelligence and operational efficiency.
- Educate cross-functional teams on ML best practices and advocate for the adoption of ML-driven approaches in product development and decision-making processes.
*Mercury is a financial technology company, not a bank. Banking services provided by Choice Financial Group and Evolve Bank & Trust®; Members FDIC.
- Have 4+ years of experience in developing and deploying machine learning models, preferably in a fintech or banking environment.
- Be proficient in SQL, Python, and other ML-related technologies, with a robust understanding of data pipelines, databases, and data visualization tools.
- Exhibit a proactive approach, capable of translating business questions into analytical problems, conducting the analysis autonomously, and effectively communicating findings to non-technical stakeholders.
- Demonstrate a keen product sensibility, understanding how ML insights can be translated into actionable product enhancements.
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