Sr. Data Scientist- Consumer Lending

STRATIVIS; United States; Hybrid; USD 130,000 - 180,000; Full time

Benefits offered by this job

Medical, dental, vision

Hybrid work environment

Casual culture

Transit access to downtown Chicago

Bike room and gym on site

Job summary

STRATIVIS is seeking a Sr. Data Scientist to join a fast-growing team in a data-driven environment. You will develop and productionize models, engineer features, and translate business needs into analytical solutions, influencing data-driven decisions across the organization.

The role emphasizes collaboration with a data science team, ongoing skill development, and opportunities to deploy and monitor models in production within a consumer lending context.

Qualifications

• Bachelor’s degree in Mathematics, Statistics, Physics, Biostatistics, Engineering or equivalent experience.
• Masters or Ph.D. preferred.
• 3 years of experience in data science.
• Experience in credit risk/ consumer lending industry is preferred.

Responsibilities

• Build, implement and maintain linear and nonlinear models.
• Perform feature engineering on new and existing datasets.
• Translate business needs into data science problems and definitions.
• Create datasets and analyses to solve business problems with actionable insights.
• Contribute to strategy and direction of data science projects.
• Complete ad-hoc analyses to improve data quality and team effectiveness.

Skills

Credit risk experience

Problem-solving

Cross-functional collaboration

Communication of analyses

Time management

Self-starter

Independent project execution

Adaptability

Education

Bachelor’s degree in Mathematics/Statistics/Physics/Biostatistics/Engineering

Masters or Ph.D. preferred

Job description

We’re seeking a Sr. Data Scientist to join our growing team. This role offers the chance to work in a fast-paced, high-growth environment where innovation, autonomy, and continuous skill development are core to how we operate. You’ll contribute across a wide range of data science initiatives using modern tools and techniques such as:

• Machine learning model development




• Advanced feature engineering




• Production model deployment, monitoring, and validation

Candidates with experience in some of these areas—and a desire to master the rest—will thrive in this role. This company offers the opportunity to build, experiment, iterate, and meaningfully influence data-driven decisions across the organization.

Who we are

We are a multi-brand online consumer lender specializing in personal loans, serving the sub-prime market. Our data science team consists of highly motivated and experienced data scientists and we are a strategic partner in developing and evolving the processes, technology, and decisions of the business. We are very collaborative - we work out difficult problems together and the work that we do has a meaningful and immediate impact on the business. We have a python-based, custom-built platform (that we designed) for running all our credit modeling, which means that we are responsible for our modeling processes from POC to production. We’re constantly working on adding new models and improving existing ones and as a member of the team you’ll have a set of models and analyses that will be your own.

Principal Responsibilities

• Build, implement and maintain a variety of linear and nonlinear models




• Perform basic and advanced feature engineering on new and existing datasets




• Turn vaguely defined business needs/problems into problem definitions




• Create datasets and perform analyses to solve business problems and provide actionable recommendations




• Provide input on the strategy and direction of data science team and projects




• Complete any ad-hoc analyses or projects that contribute to the quality of the data used and effectiveness of the data science team in general

Required Knowledge / Skills

• Experience in a data scientist role within the credit risk/ consumer lending industry




• Effective problem-solving and cross-functional collaboration skills




• Flexible and willing/able to learn new tools/methods quickly




• Detail-oriented and methodical




• Ability to communicate analysis approaches and results in an organized and clear way




• Strong multitasking skills and ability to work under pressure on several projects at a time.




• Good organization and time management skills and the ability to set priorities and accomplish objectives to meet deadlines in a fast-paced environment.




• Ability to model and promote ethical behavior.




• Ability to extrapolate from historical data and current events to anticipate business needs and plan accordingly.




• Self-starter and able to identify areas of need and jump in where needed and necessary.




• Ability to drive projects to completion independently




• Eager for new challenges and coordination with a number of different stakeholders within the organization.




• Proficiency with the following or with similar tools & platforms

Education

• Bachelor’s degree in one of the following areas of study: Mathematics, Statistics, Physics, Biostatistics, Engineering (or equivalent experience)




• Masters or Ph.D. preferred

Minimum Experience

• 3 years of experience in data science

Benefits/Perks

• Competitive pay and benefits package including medical, dental, vision




• Hybrid work environment




• Casual culture, jeans encouraged




• Work with smart, cool and dedicated folks, including Chicago’s best emerging FinTech professionals




• A fun, highly collaborative environment: you teach us, we’ll teach you




• Rapid advancement in your skillset and experience




• Convenient proximity to public transit in downtown Chicago




• Bike room and gym on site

Working Conditions/Equipment Used

• Ability to navigate computer applications and interact via phone and video conferencing platforms




• Ability to work productively from a typical, open office environment




• May require occasional weekend and/or evening work

Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.