Data Scientist 2

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).