Job
Description
About Us: DIGITAP.AI is a cutting-edge provider of AI/ML solutions for modern, internet-driven businesses. We empower clients with reliable, fast, and compliant customer onboarding, automated risk management, and big data-enabled services including Risk Analytics and Customised Scorecards. Our proprietary machine learning algorithms deliver some of the highest success rates in the market, serving India's leading digital lenders. Our vibrant team brings deep expertise in Fintech Product Development, Risk Management, Fraud Detection, and Big Data Analytics. Culture and Benefits: Innovative Start-up Environment: Shape and influence the development of industry-leading AI products in a collaborative, agile setting. Transparency and Meritocracy: Clear communication and open cultureno politics, just results and recognition. Ownership and Impact: Take initiative, think beyond your role, and make meaningful contributions to our success. Competitive Compensation: Attractive salary and potential equityyour rewards grow with the company. Role Overview: As a Senior Data Scientist specializing in NLP and ML, you will lead the design, development, and optimization of advanced AI applications, with a special focus on NLP and LLMs. Youll tackle diverse NLP use cases, contribute to ML models for credit scoring and risk assessment, and drive research and innovation in large-scale transformer models. Key Responsibilities: NLP & LLM Model Development: Build, fine-tune, and deploy advanced NLP modelsincluding text classification, document analysis, entity recognition, and sentiment analysisleveraging state-of-the-art architectures (BERT, GPT, Llama, etc.). LLM Research & Customization: Explore, adapt, and optimize pre-trained LLMs (e.g., OpenAI, Hugging Face, Llama). Credit & Risk Analytics: Develop, refine, and evaluate ML models for credit scoring, scorecard generation, and risk analytics. Data Exploration & Processing: Analyze and preprocess large amounts of unstructured text using tokenization, language normalization, embeddings, and vectorization. Deployment & Integration: Collaborate with engineering/product teams to integrate NLP/ML/LLM solutions into real-world products, ensuring scalability and reliability. Continuous Innovation: Stay current on advances in NLP, ML, and generative AI, proactively translating research breakthroughs into practical applications. Mentorship & Collaboration: Guide junior team members and collaborate across data, product, and engineering groups. Required Skills & Experience: Work Experience: 3-4 years as a data scientist, NLP engineer, or ML specialist with hands-on experience in NLP and LLMs. NLP & Deep Learning: Proven expertise in NLP tasks (text classification, entity recognition, semantic analysis) and deep learning, especially with transformer architectures. Large Language Models: Experience working with, training, and deploying LLMs (GPT, Llama, BERT, etc.). ML Frameworks: Advanced skills in Python with frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and Keras. Tooling: Experienced with libraries (NLTK, spaCy, scikit-learn, NumPy, pandas, OpenAI API). Database & API Integration: Proficient with SQL/NoSQL databases and RESTful API development/integration. Problem Solver: Strong analytical, debugging, and creative solution skills for real-world ML/NLP challenges. Regular Expressions: Hands-on expertise with text processing using regex. Preferred Qualifications: Education: BE/BTech/ME/MTech/MCA in Computer Science or related field (minimum 4-year degree). Continuous Learner: Genuine interest in ongoing research and upskilling in AI, ML, GenAI, and computer vision. Bonus Skills: Familiarity with computer vision and multimodal models.,
