Data Scientist, Credit Risk Analytics

United States Digital Space LLC; United States; Hybrid; USD 129,000 - 179,000; Full time

Benefits offered by this job

Competitive salary

Performance bonus

Health insurance

401(k) match

Job summary

United States Digital Space LLC is seeking a Data Scientist in the Credit Risk Analytics vertical. You will become a core contributor with machine learning expertise, delivering results that directly impact business value and helping shape our credit risk strategy.

This hybrid role requires building and deploying industry-leading predictive models and partnering with engineering to productionize them. You will analyze diverse data, monitor models in production, and communicate insights to Risk

Qualifications

• MS/PhD in a technical field and 2–3+ years in fintech or finance applying ML.
• 2–3+ years of work experience in fintech, finance, or another high-impact field applying statistical and ML techniques.
• Expert knowledge of Python and SQL with strong ML Ops understanding.
• Strong ability to translate technical concepts into actionable business strategies.
• Excellent cross-functional collaboration and communication skills.

Responsibilities

• Build and deploy predictive ML models for credit risk and fraud.
• Collaborate with engineering to productionize models.
• Analyze portfolio performance and identify risk drivers.
• Develop internal tools to improve DS productivity and efficiency.
• Monitor models in production and extract actionable insights.
• Evaluate new algorithms and features from diverse data sources.
• Communicate findings to Risk Management and leadership.

Skills

Python

SQL

ML techniques

Communication skills

Collaboration

Unsupervised work

Model governance

Problem solving

Finance/credit risk knowledge

Education

Master's or PhD in statistics, CS, engineering, economics or related field

Tools

ML Ops

Job description

Your role in our mission

the company is seeking a Data Scientist under the Credit Risk Analytics vertical. You will become a core contributor with machine learning expertise in the credit risk team, delivering results that directly impact business value. This is a unique, hybrid role where you will not only build and deploy industry-leading predictive models but also play a critical role in shaping our credit risk strategy and business decisions.

How you’ll make an impact

• Build industry-leading machine learning models for managing credit and fraud risks. Collaborate closely with engineering to deploy models into a production environment.
• Leverage complex data sources (e.g., credit bureau reports, customer-supplied information) at scale to develop credit and fraud strategies to improve the credit performance and optimize risk decisions.
• Propose and execute strategic solutions to complex business problems, operating effectively within constraints and aligning with broader company objectives.
• Analyze ad-hoc portfolio performance at a granular segment level on an ongoing basis. Identify trends and conduct root-cause analysis to isolate key performance drivers. Communicate findings and recommendations to the Risk Management and broader the company community.
• Help the team develop internal tools and workflow solutions to increase data science productivity and operational efficiency.
• Actively monitor credit risk models and strategies in production, extracting actionable insights to significantly impact key business metrics.
• Assess the potential usefulness and validity of new machine learning algorithms and features sourced from diverse, alternative data providers.
• Conduct high-impact, ad-hoc analyses supporting risk management, investor services, operations, and corporate development initiatives.

Skills that will help you thrive

• 2-3+ years of work experience in fintech, finance, or another high-impact field applying statistical and machine learning predictive techniques. Consumer lending experience in unsecured personal loans or credit cards is a strong plus.
• Advanced degree (M.S./Ph.D.) preferably in statistics, computer science, engineering, physical sciences, economics, or a related technical field.
• Expert knowledge of statistical programming languages (e.g., Python) and database languages (e.g., SQL).
• Solid understanding of coding best practices, model documentation, and ML ops principles.
• Strong communication skills with the ability to translate complex technical subject matter into clear, actionable business strategies for cross-functional partners and senior management.
• Strong ability to collaborate seamlessly with people across various functions (engineering, product, compliance) and build strong relationships.
• Ability to work unsupervised in a fast-paced environment, effectively prioritizing among parallel technical and strategic projects.
• Ability to innovate within regulatory guidelines with a strong commitment to reproducible research and model governance.
• Self-motivated, results-oriented, enthusiastic, and a creative thinker who bridges the gap between data science and business strategy.

Resources to help you the company

• A connected experience: We prioritize high-touch collaboration and flexibility. Whether you are working from our San Francisco or Phoenix offices or joining us as a fully remote team member, we provide the digital-first tools and intentional culture to keep you synced and supported
• Invested in your future: A competitive salary and a 401(k) with a 5% company match to help you build long-term financial security
• Holistic well-being: We provide the resources you need to thrive, from flexible time off and paid parental leave to an annual wellness allowance and comprehensive health coverage
• Professional & personal growth: Take advantage of a suite of premium perks, including Udemy access, childcare assistance, pet insurance, and a bevy of additional savings through Beneplace

Interview Process

• Recruiter Call: A brief screening to discuss your experience and initial questions.
• Department Interview: Deeper dive into technical skills and project alignment with the Hiring Manager or team member.
• Team/Virtual Interview: Meet team members for collaborative discussions, problem-solving, or technical exercises.
• Final Round: Discussion with a department head/executive.

Compensation details: The salary for this position is $129,000 - $179,000 annually, plus bonus and generous benefits. In determining your salary, we will consider your location, experience, and other job-related factors. #LI-SK1#LI-Remote

About Us

the company introduced U.S. consumers to an innovative approach to personal finance as the first peer-to-peer lending platform in the country. Since 2005, the company has helped over 2 million customers achieve financial well-being through a comprehensive suite of digital personal finance products.

the company’s flagship personal loan marketplace continues to offer unique value for both borrowers and investors, while the company® Card¹ provides essential access to credit and flexibility for those managing their financial journey. Guided by its mission to advance financial well-being, the company is dedicated to helping people thrive by meeting people where they are with simple, trusted, and affordable financial solutions. Learn more at www.thecompany.com.

We’re on a mission to hire the very best, and we are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere. It is important to us that every hire connects with our vision, mission, and core values. Join a leading fintech company that’s democratizing finance for all!

Our Values

• Diversity expands opportunities
• Collaboration creates better solutions
• Curiosity fuels our innovation
• Integrity defines all our relationships
• Excellence leads to longevity
• Simplicity guides our user experience
• Accountability at all levels drives results

www.thecompany.com Our Story & Team Our Blog

Applicants have rights under Federal Employment Laws. Family & Medical Leave Act (FMLA) Equal Employment Opportunity (EEO) Employee Polygraph Protection Act (EPPA)

California applicants: please click here to view our California Consumer Privacy Act (“CCPA”) Notice for Applicants, which describes your rights under the CCPA.

Illinois applicants: please click here to view our Artificial Intelligence Notice for Applicants. At the company, we're looking for people with passion, integrity, and a hunger to learn. We encourage you to apply even if your experience doesn't precisely match the job description. Your unique skill set and diverse perspective will stand out and set you apart from other candidates. the company thrives with people who think outside of the box and aren't afraid to challenge the status quo. We invite you to join us on our mission to advance financial well-being.

the company is committed to an inclusive and diverse workplace. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law, including the San Francisco Fair Chance Ordinance. the company will consider for employment qualified applicants who are non-US citizens and will provide green card sponsorship.

• All personal loans are made by WebBank.

¹The company® Card is an unsecured credit card issued by Coastal Community Bank, Member FDIC, pursuant to license by Mastercard® International.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.