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:
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Innovative Start-up Environment: Enjoy the flexibility to design, implement, and influence the development of cutting-edge solutions.
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Transparency and Meritocracy: We value clear communication, eschew politics, and promote an open culture where contributions are recognized and rewarded.
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Ownership and Impact: We encourage team members to take ownership, think beyond their roles, and contribute to the company's success in meaningful ways.
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Competitive Compensation: We offer a competitive salary and a potential equity package, aligning your success with the company's growth.
Key Responsibilities
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Assist in developing machine learning models for credit scoring, fraud detection, and risk prediction
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Work with large datasets for data cleaning, preprocessing, and feature engineering
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Support model experimentation, evaluation, and performance optimization
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Contribute to building automated ML pipelines for data processing and model training
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Monitor model performance and data drift in production systems
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Collaborate with data scientists, engineers, and product teams to translate business problems into ML solutions
Required Skills
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1+ year experience working with Machine Learning models (classification/regression)
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Strong Python programming skills
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Experience with NumPy, Pandas, Scikit-learn, Matplotlib/Seaborn
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Knowledge of model evaluation, cross-validation, overfitting, and feature importance
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Experience with data cleaning, preprocessing, and feature engineering
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Basic SQL querying skills
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Familiarity with Git and collaborative development
Preferred Qualifications
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Degree in Computer Science, Data Science, Mathematics, or related field
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Exposure to Fintech / Credit Risk / Business Analytics
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Basic understanding of MLOps, model deployment, or pipeline automation
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Passion for learning new ML tools and technologies
