About Digitap.ai:
DIGITAP.AI is an Enterprise SaaS company providing high-tech advanced AI/ML, Alternate Data Solutions to new-age internet-driven businesses for reliable, fast, and 100% compliant Customer Onboarding, Alternate Data Solutions for Automated Risk Management, and other Value-Added Services. Our proprietary Machine Learning Algorithms and Modules provide one of the best success rates in the market. We work with the top digital lenders of India & the team brings together deep and vibrant experience in Fintech Product & Risk Management, Fraud Detection, and Risk Analytics.
Culture and Benefits:
Innovative Start-up Environment: Enjoy the flexibility to design, implement, and influence the development of cutting-edge solutions.
Transparency and Meritocracy: We value clear communication, eschew politics, and promote an open culture where contributions are recognized and rewarded.
Ownership and Impact: We encourage team members to take ownership, think beyond their roles, and contribute to the company's success in meaningful ways.
Competitive Compensation: We offer a competitive salary and a potential equity package, aligning your success with the company's growth.
Job Description:
Key Responsibilities
Assist in developing machine learning models for credit scoring, fraud detection, and risk prediction
Work with large datasets for data cleaning, preprocessing, and feature engineering
Support model experimentation, evaluation, and performance optimization
Contribute to building automated ML pipelines for data processing and model training
Monitor model performance and data drift in production systems
Collaborate with data scientists, engineers, and product teams to translate business problems into ML solutions
Required Skills
1+ year experience working with Machine Learning models (classification/regression)
Strong Python programming skills
Experience with NumPy, Pandas, Scikit-learn, Matplotlib/Seaborn
Knowledge of model evaluation, cross-validation, overfitting, and feature importance
Experience with data cleaning, preprocessing, and feature engineering
Basic SQL querying skills
Familiarity with Git and collaborative development
Preferred Qualifications
Degree in Computer Science, Data Science, Mathematics, or related field
Exposure to Fintech / Credit Risk / Business Analytics
Basic understanding of MLOps, model deployment, or pipeline automation
Passion for learning new ML tools and technologies