Data Scientist
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 23d ago
The date the source published, not the day we noticed it (2026-09-17). Last seen at its source 3h ago.
We have tracked this listing since 9 Oct 2026 (1 days). The employer's own board has carried it every time we have read it, most recently 3 hours ago.
Is it remote?
Remote, United States
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $105k–184.5k/yr
Middle 50% of 1293 listings that do state pay — Operations · all levels · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
Greenhouse employer's own board first seen 1d ago · last seen 3h ago
The listing
Who is Credible?
Credible is a leading U.S. consumer finance marketplace, transforming the way consumers access and compare financial products. We operate at a consumer and enterprise level. On the consumer side, we help millions of people make smarter financial decisions by comparing personalized, pre-qualified offers across student loans, personal loans, mortgages, credit cards, and insurance — all without impacting their credit score. On the enterprise side, we power financial product comparison and distribution through deep integrations and partnerships with lenders, insurance carriers, and financial institutions, as well as providing marketplace technology and capabilities to third-party partners and distribution channels.
About the role
Our Business Intelligence and Analytics team is seeking to grow the company’s Data Science and Machine Learning capabilities across several facets of our business. We are seeking a seasoned Data Scientist to lead this transformative step change function and nurture its growth across several focus areas. You will drive tactical and strategic execution of several data science projects and manage their entire lifecycle.
You will:
- Drive the long-term statistical modeling and machine learning vision of the company.
- Conducting exploratory data analysis (EDA) prior to model development
- Performing feasibility assessments (POCs) for proposed ML solutions
- Monitoring and diagnosing model performance issues, including drift and degradation
- Researching and evaluating additional use cases for existing models
- Supporting ad hoc ML-related analytics requests from stakeholders and senior data scientists
- Conduct analysis to develop and improve our product recommendation and user classification systems. Use this understanding to help optimize our adaptive user experience, cross selling initiatives, and retargeting efforts.
- Design, prototype, and implement models across several domains. Manage each part of a project’s life cycle, including ad-hoc exploration, preparation of training data, model development, and production deployment.
- Work with product and marketing managers, analysts, and engineers to turn insights about our users into automated services.
Education and Experience:
- BA/BS in Mathematics, Statistics, or Computer Science required. Masters Degree in a quantitative or scientific discipline strongly desired.
- 3+ years experience in developing, testing, and deploying optimized predictive models (preferably to inform in-product recommendation systems and automated customer re-targeting efforts).
- Advanced statistical modeling skillset (Python, R, etc).
- Advanced SQL querying, data mining, and data cleansing skillset.
- Deep knowledge of supervised and unsupervised machine learning algorithms (neural networks, decision trees, etc.).
- Advanced knowledge of experiment design.
- Experience with Seldon-core or other MLOps tools is preferred.
- Hands-on experience with cloud infrastructure tools (AWS EC2, S3, Redshift, Snowflake, containers).
- Advanced visualization/reporting and presentation experience.
- Version Control Experience (GitHub).
- Demonstrated experience adopting and effectively leveraging AI tools in day-to-day data science workflows.
- Familiarity with ML deployment infrastructure (ETL, tools, new products in the space).
- Excellent strategic project planning skillset.
- Excellent communication skills (written and verbal).
- Experience at an e-commerce or fintech company is a plus.
Must Haves:
- Ability to develop project plans and deliver results against quarterly and annual roadmaps.
- Comfortable working with loosely defined requirements where you exercise your creativity and analytical skills to deliver best in class solutions.
- Excellent written and verbal communication. Ability to articulate vision, complex thoughts, analytical processes, and results in clear business terms.
- Anticipate business needs and think with a business owner mindset – think critically about analyses and solutions and provide improvement recommendations. This role requires an individual who can work autonomously.
Pursuant to state and local pay disclosure requirements, the pay ranges for this role, with final offer amount dependent on education, skills, experience, and location, are listed below. This role is also eligible for an annual discretionary bonus, various benefits, including medical/dental/vision, insurance, a 401(k) plan, paid time off, and other benefits in accordance with applicable plan documents.
View more details about Credible Benefits
We combine the intelligence, expertise, and confidence of a financial advisor with the approachability and honesty of a friend. In other words, we’re the friend you always wish you had in finance.
We are optimistic, challengers, trustworthy, clever, and smart. We are open and transparent. We strive to act as advisors by being friendly, objective, and open in our communication. We use language that is intelligent yet approachable. When appropriate, we’ll drop in a bit of wit to position ourselves as a fresh, reliable voice in the financial world.