Data Scientist

Job Description

Assist in designing, fine-tuning, and optimizing LLMs for agentic workflows, content generation, and recommendation systems. Conduct data preprocessing, feature engineering, and exploratory analysis to enhance model performance. Implement and experiment with advanced deep learning techniques, including reinforcement learning and prompt engineering, for generative AI applications. Support deployment of ML models into production environments. Help build monitoring tools to track model performance and data drift. Work with cross-functional teams (engineers, product managers) to deliver high-quality AI solutions. Document processes and present findings to stakeholders. Stay updated on advancements in generative AI, NLP, and ML frameworks (e.g., PyTorch, Hugging Face). Participate in code reviews and adopt best practices in ML ops. You ve Got What It Takes If You Have Programming: Python (pandas, NumPy), SQL ML/NLP: Familiarity with PyTorch, transformers, embeddings, and attention mechanisms and basics of GenAI Tools: Git, Docker, cloud platforms (AWS /GCP) Data: Handling Data cleaning, preprocessing, and visualization (Matplotlib/Seaborn) Deployment: Basic knowledge of REST APIs, CI/CD pipelines Soft Skills Collaborative Mindset: Team player who thrives in a fast-paced, results-driven environment. Adaptability: Willingness to learn new tools/technologies (e.g., LangChain, vector databases). Problem-Solving: Analytical thinker with attention to detail. Communication: Ability to explain technical concepts to non-technical stakeholders. Qualifications Education: Bachelor s degree in Computer Science, Data Science, or related field. Experience: 0-2 years in ML/NLP projects (academic/internship experience accepted). Extra dose of awesome if you have... Certifications in ML/AI (e.g., TensorFlow Developer, AWS ML Specialty). Exposure to generative AI tools (e.g., GPT, Claude, Llama).