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Data Scientist

Pay
Pay not listedSimilar roles state $118K–$193K
Work setting
Remote — work setting source
Listed location: Remote, United States
Read the full posting
Employment
Not stated

What you’ll work on

Full posting

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.

Drive the long-term statistical modeling and machine learning vision of the company.

  • Own data science projects from exploration and training data through production deployment

  • Develop and improve product recommendation and user classification systems

  • Monitor model performance and diagnose drift and degradation

  • Run feasibility assessments (POCs) for proposed ML solutions

  • Turn insights about users into automated services with product and marketing teams

From the employer’s posting
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.
Drive the long-term statistical modeling and machine learning vision of the company.
Manage each part of a project’s life cycle, including ad-hoc exploration, preparation of training data, model development, and production deployment.
Conduct analysis to develop and improve our product recommendation and user classification systems.
Monitoring and diagnosing model performance issues, including drift and degradation
Performing feasibility assessments (POCs) for proposed ML solutions
Work with product and marketing managers, analysts, and engineers to turn insights about our users into automated services.

What you’ll bring

All qualifications

Core experience

  • 3+ years experience in developing, testing, and deploying optimized predictive models (preferably to inform in-product recommendation systems and automated customer re-targeting efforts).
  • Ability to develop project plans and deliver results against quarterly and annual roadmaps.
  • Deep knowledge of supervised and unsupervised machine learning algorithms (neural networks, decision trees, etc.).
  • Ability to articulate vision, complex thoughts, analytical processes, and results in clear business terms.
  • Hands-on experience with cloud infrastructure tools (AWS EC2, S3, Redshift, Snowflake, containers).
  • Demonstrated experience adopting and effectively leveraging AI tools in day-to-day data science workflows.

Preferred experience

  • Experience with Seldon-core or other MLOps tools is preferred.
  • Experience at an e-commerce or fintech company is a plus.
Qualification wording
3+ years experience in developing, testing, and deploying optimized predictive models (preferably to inform in-product recommendation systems and automated customer re-targeting efforts).
Ability to develop project plans and deliver results against quarterly and annual roadmaps.
Deep knowledge of supervised and unsupervised machine learning algorithms (neural networks, decision trees, etc.).
Excellent written and verbal communication. Ability to articulate vision, complex thoughts, analytical processes, and results in clear business terms.
Hands-on experience with cloud infrastructure tools (AWS EC2, S3, Redshift, Snowflake, containers).
Demonstrated experience adopting and effectively leveraging AI tools in day-to-day data science workflows.
Experience with Seldon-core or other MLOps tools is preferred.
Experience at an e-commerce or fintech company is a plus.
Education & alternatives
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).
Apply at Credible

Posting record

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Status in our records
Live
First seen by us
Sep 22, 202643 days ago
Recorded sightings
26
Last seen by us
Nov 4, 2026
Employer says posted
Sep 17, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$193K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,721 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 43

Similar jobs usually come down between day 7 and day 55.

From 9,990 similar postings that came down. Coming down is not always a hire.

Credible is hiring

3 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • R
  • SQL
  • AWS
  • Redshift
  • S3
  • Snowflake
Where the posting names them
- 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.
- 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.).
- 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.

Your next step

Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.

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About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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

For high cost of labor markets such as but not limited to New York City and San Francisco:
$102,000—$136,000 USD
For all other US locations:
$89,000—$124,000 USD
Why work at Credible?

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.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, gender identity, disability, protected veteran status, or any other characteristic protected by law. We will consider for employment qualified applicants with criminal histories consistent with applicable law.
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Remote, United States

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