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Descripción De La Posición

Job Title -  S&C GN  - Data Science Consultant

Team: Global Network – Data & AI

Practice: Health Analytics  

Location: Bengaluru, Gurugram, Mumbai, Kolkata, Pune, Chennai, Hyderabad

Experience: 4-8 Years in Healthcare Analytics

Educational Qualification:

  • Master’s degree in computer science, statistics, applied mathematics, or a related field with 3+ years of experience, OR
  • Bachelor’s degree in computer science, statistics, applied mathematics, or a related field with 4+ years of experience

We are an innovative Data Science team specializing in the Contact Center domain, dedicated to transforming customer interactions through data-driven intelligence. As part of the Marketing Analytics team, we focus on optimizing contact center operations by leveraging machine learning, natural language processing (NLP), generative ai, and advanced analytics.

Our work involves analyzing customer conversations, predicting user behavior, and enhancing self-service capabilities to reduce call transfers and improve satisfaction. We build conversational AI models, real-time recommendation systems, and predictive analytics solutions that drive meaningful business impact. By integrating AI-driven insights with marketing strategies, we enable proactive customer engagement, personalized experiences, and operational efficiencies across various touchpoints.

This role involves driving strategic initiatives, managing business transformations, and leveraging industry expertise to create value-driven solutions.

If you're passionate about applying data science to solve real-world customer experience challenges, this is the team for you!

Key Responsibilities

As a Data Science Consultant, you will:

  • Develop and fine-tune Generative AI models to automate responses and improve customer interactions.
  • Build and deploy ML models for intent classification, sentiment analysis, and predictive analytics.
  • Apply NLP techniques (NER, summarization, embeddings) using frameworks like Hugging Face, LangChain, and OpenAI APIs.
  • Optimize conversational AI workflows for real-time decision-making and enhanced self-service.
  • Analyze large-scale customer interaction data to extract actionable insights.
  • Work with unstructured data (text, audio, chat, emails) to build robust AI/ML pipelines.
  • Collaborate with cross-functional teams (engineering, product, marketing) to integrate AI solutions.
  • Leverage cloud platforms (Azure, AWS, GCP) for scalable AI/ML development and deployment.

What you would do in this role

  • Work with Managers to get Client's business requirements and deliver Analytics driven solution.
  • Duties and Responsibilities:
    • Sr. Data Scientist is responsible for generating actionable recommendations well-supported by quantitative analysis to help our clients address their ongoing problems.
    • Present analytic findings & opportunities for improvement to senior management and summarize key findings, and aid in the dissemination of metrics throughout the organization.
    • Build knowledge base and disseminate information on applications of variety of analytical techniques.
    • Develop statistical models and delivery of analytic offerings and solutions in health domain areas.

Requisitos

Required Skills

Technical Must-Haves

  • Python programming
  • Advanced data manipulation (Pandas, NumPy)
  • SQL or PySpark
  • Machine Learning & Deep Learning (Scikit-learn, PyTorch/TensorFlow)
  • NLP and NLP Frameworks (NER, summarization, embeddings, Hugging Face, LangChain)
  • Generative AI (LLMs, Transformers, Diffusion Models)
  • Retrieval-Augmented Generation (RAG)
  • Prompt Engineering
  • Unstructured Data Handling (text, chat, emails)

Good to Have Skills

  • LLM Optimization (fine-tuning, prompt engineering, efficient deployment)
  • Experience with cloud-native AI/ML services (Azure ML, AWS Sagemaker, GCP Vertex AI)
  • Customer segmentation and behavioral analysis
  • Conversational AI optimization
  • Large-scale data analysis
  • Agentic AI (multi-agent orchestration, memory, autonomous workflows)
  • Unstructured Data Handling (audio)


 

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