Data Scientist 2

1 day ago

Yelahanka, India Licious Full time

Data Scientist Licious is a fast-paced, innovative D2C brand revolutionizing the meat and seafood industry in India. We leverage cutting-edge technology, data science, and customer insights to deliver unmatched quality, convenience, and personalization. Join us to solve complex problems at scale and drive data-driven decision-making Role Overview: We are seeking a Data Scientist with 5+ years of experience to build and deploy advanced ML models (LLMs, Recommendation Systems, Demand Forecasting) and generate actionable insights. You will collaborate with cross-functional teams (Product, Supply Chain, Marketing) to optimize customer experience, demand prediction, and business growth. Key Responsibilities: 1. Machine Learning & AI Solutions: ● Develop and deploy Large Language Models (LLMs) for customer support automation, personalized content generation, and sentiment analysis. ● Enhance Recommendation Systems (collaborative filtering, NLP-based, reinforcement learning) to drive engagement and conversions. ● Build scalable Demand Forecasting models (time series, causal inference) to optimize inventory and supply chain. 2. Data-Driven Insights: ● Analyze customer behavior, transactional data, and market trends to uncover growth opportunities. ● Create dashboards and reports (using Tableau/Power BI) to communicate insights to stakeholders. 3. Cross-Functional Collaboration: ● Partner with Engineering to productionize models (MLOps, APIs, A/B testing). ● Work with Marketing to design hyper-personalized campaigns using CLV, churn prediction, and segmentation. 4. Innovation & Scalability: ● Stay updated with advancements in GenAI, causal ML, and optimization techniques. ● Improve model performance through feature engineering, ensemble methods, and experimentation. Qualifications: ● Education: BTech/MTech/MS in Computer Science, Statistics, or related fields. ● Experience: 4+ years in Data Science, with hands-on expertise in: ○ LLMs (GPT, BERT, fine-tuning, prompt engineering). ○ Recommendation Systems (matrix factorization, neural CF, graph-based). ○ Demand Forecasting (ARIMA, Prophet, LSTM, Bayesian methods). ○ Python/R, SQL, PySpark, and ML frameworks (TensorFlow, PyTorch, scikit- learn). ○ Cloud platforms (AWS/GCP) and MLOps tools (MLflow, Kubeflow).

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