Data Analyst
Skeps provides an enterprise credit orchestration and pay-over-time platform for merchants and financial institutions. Its platform connects businesses with multiple lending partners, delivers real-time pre-qualified financing offers, and supports embedded financing across online, in-store, POS, contact-center, and in-home sales channels.
Funding history
Investors
About Skeps
Skeps operates a lender-neutral enterprise platform that helps merchants and financial institutions manage financing programs, lender selection, routing strategies, reporting, and customer experiences. Its capabilities include Parallel Look multi-lender matching, digital prescreening, fraud and KYC/KYB workflows, digital cards, A/B testing, consumer UX customization, loan origination and management systems, and integrated servicing support. Skeps serves enterprise organizations in home improvement, retail, travel and hospitality, healthcare, veterinary, automotive, telecom, and other high-value industries.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will interpret and analyse data using statistical techniques and provide ongoing reports. You will build reporting infrastructure, interactive dashboards, and analytical tools; acquire data; identify data-system issues and trends; develop regression and forecasting models; and identify process improvements.
Requirements
- Bachelor’s or Master’s degree in statistics, mathematics, or engineering.
- 2+ years of experience as a Data Analyst or Business Data Analyst.
- Technical expertise in data models, database design and development, data mining, and segmentation techniques.
- Knowledge of Excel, SQL, Python, and dashboarding tools such as Metabase and Tableau.
- Knowledge of statistics and experience with Pandas, NumPy, scikit-learn, and Seaborn.
- Experience developing regression and forecasting models using historical data.
- Strong analytical skills for collecting, organizing, analysing, and disseminating information.
Responsibilities
- Interpret data, analyse results using statistical techniques, and provide ongoing reports.
- Develop reporting infrastructure, interactive dashboards, and analytical tools.
- Acquire data from primary and secondary sources and identify issues in databases and data systems.
- Identify and interpret trends and patterns in complex datasets.
- Develop regression and forecasting models using historical data.
- Work with management to prioritize business and information needs.
- Identify process improvement opportunities.