Data Mining Associate

Company Description BeFiSc is a fraud detection company that reveals risks hidden in polished documents and digital interactions. The organization helps businesses verify identities, detect document tampering, and uncover true financial behavior in statements and related data. Its technology surfaces red flags that humans and legacy systems often miss, including forged identities, edited PDFs, and unsafe communication channels. BeFiSc supports fraud defenses for over 150 companies, enabling more confident decision-making. The company operates with a clear mission: in a world where trust must be verified, BeFiSc flags what is risky.

Role Description The Data Mining Associate internship at BeFiSc is an on-site role based in Delhi, India. Interns will assist in collecting, cleaning, and organizing large datasets used to detect fraud and assess risk in financial and identity-related information. Day-to-day tasks include running data queries, supporting data analysis workflows, preparing structured datasets for modeling, and documenting data sources and processes. The role also involves collaborating with senior data professionals, summarizing findings for internal stakeholders, and contributing to continuous improvement of data quality and reporting. This internship is designed to provide hands-on experience in data-driven fraud detection and decision support.

Qualifications

• Candidates should possess strong Analytical Skills and the ability to interpret complex patterns and trends.
• Candidates should possess effective Communication skills for clear reporting and collaboration with cross-functional teams.
• Candidates should possess Data Analytics and Data Science skills to support data-driven fraud detection and risk assessment.
• Candidates should possess Data Management skills to handle, structure, and maintain large, diverse datasets.
• Basic knowledge of SQL, Python, or R and familiarity with data visualization tools is beneficial.
• Currently pursuing or having completed a degree in Data Science, Statistics, Computer Science, Engineering, or a related field is preferred.
• Attention to detail, integrity in handling sensitive data, and a willingness to learn in a fast-paced environment are important.