Data Scientist

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., 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.

• 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.

Posted Yesterday Remote Hiring Remotely in United States 102K-136K Annually Mid level Remote Hiring Remotely in United States 102K-136K Annually Mid level Develop and lead data science and machine learning initiatives, including exploratory analysis, predictive modeling, experimentation, recommendation systems, user classification, model monitoring, and production deployment. Partner with product, marketing, analytics, and engineering teams to convert user insights into automated services. Manage projects throughout their lifecycle, support strategic ML planning, and deliver solutions for personalization, cross-selling, and retargeting. The summary above was generated by AI, 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?

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.