Key Responsibilities:

1. Machine Learning &amp; AI Solutions:

<ul>
<li style="margin-left:0px;">Develop and deploy Large Language Models (LLMs) for customer support automation, personalized content generation, and sentiment analysis.</li>
</ul>

<ul>
<li style="margin-left:0px;">Enhance Recommendation Systems (collaborative filtering, NLP-based, reinforcement learning) to drive engagement and conversions.</li>
</ul>

<ul>
<li style="margin-left:0px;">Build scalable Demand Forecasting models (time series, causal inference) to optimize inventory and supply chain.</li>
</ul>

2. Data-Driven Insights:

<ul>
<li style="margin-left:0px;">Analyze customer behavior, transactional data, and market trends to uncover growth opportunities.</li>
</ul>

<ul>
<li style="margin-left:0px;">Create dashboards and reports (using Tableau/Power BI) to communicate insights to stakeholders.</li>
</ul>

3. Cross-Functional Collaboration:

<ul>
<li style="margin-left:0px;">Partner with Engineering to productionize models (MLOps, APIs, A/B testing).</li>
</ul>

<ul>
<li style="margin-left:0px;">Work with Marketing to design hyper-personalized campaigns using CLV, churn prediction, and segmentation.</li>
</ul>

4. Innovation &amp; Scalability:

<ul>
<li style="margin-left:0px;">Stay updated with advancements in GenAI, causal ML, and optimization techniques.</li>
</ul>

<ul>
<li style="margin-left:0px;">Improve model performance through feature engineering, ensemble methods, and experimentation.</li>
</ul>

Qualifications:

<ul>
<li style="margin-left:0px;">Education: BTech/MTech/MS/Ph.D. in Computer Science, Statistics, or related fields.</li>
</ul>

<ul>
<li style="margin-left:0px;">Experience: 6+ years in Data Science, with hands-on expertise in:</li>
</ul>

<ul>
<li style="margin-left:0px;">LLMs (GPT, BERT, fine-tuning, prompt engineering).</li>
</ul>

<ul>
<li style="margin-left:0px;">Recommendation Systems (matrix factorization, neural CF, graph-based).</li>
</ul>

<ul>
<li style="margin-left:0px;">Demand Forecasting (ARIMA, Prophet, LSTM, Bayesian methods).</li>
</ul>

<ul>
<li style="margin-left:0px;">Python/R, SQL, PySpark, and ML frameworks (TensorFlow, PyTorch, scikit-learn).</li>
</ul>

<ul>
<li style="margin-left:0px;">Cloud platforms (AWS/GCP) and MLOps tools (MLflow, Kubeflow). </li>
</ul>

Lead Data Scientist

Key Responsibilities: 1. Machine Learning &amp; 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 &amp; 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/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).

Lead Data Scientist in Bengaluru

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Job Description

Job Description for Lead Data Scientist

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