Data Scientist - Network Value

Plaid·Remote(San Francisco HQ)

Data & Analytics

Excel

WFA Digital Insight

As the demand for data-driven insights in fintech continues to soar, with a reported 25% increase in data scientist roles in the past year, professionals with a strong foundation in analytics and machine learning are in high demand. Plaid, a pioneer in financial technology, is seeking a skilled Data Scientist to enhance its network value, making this an exciting opportunity for those who can bridge the gap between complex data and business strategy. With thousands of companies, including Venmo and SoFi, relying on Plaid's services, the successful candidate will have the chance to work on impactful projects, driving innovation in financial services. Before applying, candidates should be prepared to showcase their ability to turn complex data into actionable insights and their experience with SQL, Python, and data modeling tools.

Job Description

About the Role

The Data Scientist position at Plaid is a key role within the Network Value Data Science team, focused on enhancing the company's fintech consumer network by increasing access to, authorization for, and usability of users' financial footprints. This entails working closely with product teams to support OKRs and product roadmaps, identifying opportunities for product improvement, and championing a data-first decision-making approach. The role requires a unique blend of technical expertise, business acumen, and collaboration skills to drive impactful outcomes. As part of Plaid's commitment to empowering a healthier financial life for millions, the Data Scientist will embed within product teams to translate ambiguous product questions into tractable analysis. This involves serving as an analytical thought partner, identifying opportunities to build better products, and driving a data-first culture across the organization. The successful candidate will have a strong track record of turning complex data into strategic insights and measurable business impact. Plaid's dedication to innovation and customer empowerment creates a dynamic work environment where data scientists can make a significant difference. With a network covering 12,000 financial institutions across the US, Canada, UK, and Europe, the potential for growth and impact is substantial.

What You Will Do

Perform ad-hoc and strategic analyses to uncover opportunities for improved business outcomes and translate complex questions into actionable analytics projects.
Design and maintain scalable data models and dashboards that increase visibility into core systems and drive operational excellence.
Build and iterate on machine learning prototypes to power insight-driven products and unlock new sources of customer and business value.
Define and track OKRs that quantify progress toward key business goals, ensuring alignment and accountability across teams.
Design and analyze experiments to guide product decisions and optimize feature launches.
Collaborate with cross-functional teams to ensure data quality, integrity, and reliability, driving a culture of data excellence.
Develop and maintain data pipelines and metrics frameworks using tools such as Airflow and dbt.
Champion a data-first culture by promoting analytical rigor and evidence-based decision-making across the organization.
Stay up-to-date with industry trends, emerging technologies, and best practices in data science and analytics, applying this knowledge to continuously improve Plaid's data capabilities.
Partner with product managers to develop and prioritize product roadmaps based on data insights and customer needs.
Communicate complex data insights and recommendations to both technical and non-technical stakeholders, influencing product and business decisions.

What We Are Looking For

2+ years of experience as a Data Scientist or in a related analytics or data-focused role.
Strong track record of turning complex data into strategic insights and measurable business impact.
Proven ability to use experimentation, advanced analytics, and data storytelling to uncover opportunities that drive key product and business outcomes.
Strong technical foundation in SQL and Python for large-scale analysis, data modeling, and ML prototyping.
Experience developing and maintaining data pipelines and metrics frameworks using tools such as Airflow and dbt.
Background working with complex backend systems and large datasets.
Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.
Strong understanding of data visualization principles and the ability to communicate insights effectively to various audiences.
Experience with cloud-based data platforms and machine learning technologies.

Nice to Have

Experience with financial data and banking systems, with an understanding of financial regulations and compliance.
Knowledge of additional programming languages such as R or Julia.
Certification in data science, machine learning, or a related field.
Experience with agile development methodologies and version control systems like Git.

Benefits and Perks

Competitive salary and equity package.
Comprehensive health, dental, and vision insurance.
Generous PTO policy and flexible work hours.
Access to professional development opportunities, including conferences, workshops, and online courses.
State-of-the-art equipment and tools to support your work.
Remote work stipend to support your home office setup.
Annual budget for learning and development to help you grow professionally.
Access to a vibrant community of professionals in the fintech industry, with opportunities for networking and collaboration.

How to Stand Out

Ensure your resume and cover letter are tailored to highlight your experience with data modeling, machine learning, and SQL, as these are key skills for the role.
Be prepared to provide specific examples of how you have used data to drive business decisions and outcomes in your previous roles.
Familiarize yourself with Plaid's products and services, and be ready to discuss how your skills and experience align with the company's goals and mission.
Practice explaining complex data insights and technical concepts in simple, non-technical terms, as this is a key part of the Data Scientist role.
Consider creating a portfolio or GitHub repository showcasing your data science projects and accomplishments to share with the interviewer.
Prepare thoughtful questions to ask the interviewer about the role, team, and company culture, demonstrating your interest in the position and willingness to learn.

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