Data Analyst
Skeps provides an embedded financing platform for enterprise merchants and financial institutions. Its technology connects customers to real-time, pre-qualified offers from multiple lenders across online, in-store, and direct sales journeys.
Funding
Investors
About Skeps
Skeps is a microservices platform that embeds banking and financing services into merchant websites, retail stores, and one-to-one sales flows. It enables merchants to control lender networks, pricing, financing programs, reporting, and customer experiences for higher-value purchases across home improvement, retail, telecom, travel, health and wellness, automotive, and veterinary sectors. For financial institutions, Skeps provides configurable modules for credit eligibility, fraud and KYC/KYB workflows, digital cards, testing, loan origination, loan management, and multi-lender programs.
Skills
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.
