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 culture no 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 equity your 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. You ll 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 models including text classification, document analysis, entity recognition, and sentiment analysis leveraging 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.
Skills:
MACHINE LEARNING, NATURAL LANGUAGE PROCESSING, LARGE LANGUAGE MODELS, PYTHON, PYTORCH, TENSORFLOW, HUGGING FACE TRANSFORMERS, KERAS, NLTK, SPACY, SCIKIT-LEARN, PANDAS, OPENAI API, SQL, NOSQL, API INTEGRATION, RESTFUL APIS, PROBLEM-SOLVING, COMPUTER VISION (PLUS) 
