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Licious - Lead Data Scientist - Machine Learning

DELIGHTFUL GOURMET PRIVATE LIMITEDBangalore

30+ days ago

Job description

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 Lead Data Scientist with 6+ 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 :

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.

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 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.

Innovation & Scalability :

Stay updated with advancements in GenAI, causal ML, and optimization techniques.

Improve model performance through feature engineering, ensemble methods, and :

Education : BTech / MTech / MS / Ph.D in Computer Science, Statistics, or related fields.

Experience : 6+ 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).

(ref : hirist.tech)

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