Senior Data Scientist / AI/ML

Wnsglobalservices144

Gurugram District

On-site

INR 2,500,000 - 4,200,000

Full time

6 days ago
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Job summary

Wnsglobalservices144 is seeking a seasoned leader in Advanced Analytics for Lifesciences/Pharma to head a dynamic team delivering AI-driven analytics across Marketing, Sales, Medical and Commercial Operations.

Proficiency in Machine Learning, Deep Learning, NLP, Generative AI and Large Language Models (LLMs), plus Python/PySpark, is essential to devise scalable analytics solutions and measurable business value.

Qualifications

  • 4-10 years of experience in Advanced Analytics, Data Science or AI.
  • 2-4 years of experience in Healthcare, Lifesciences or Pharmaceutical Analytics is preferred.
  • Strong quantitative, analytical and problem-solving skills.
  • Ability to quickly translate datasets into business insights.
  • Experience delivering measurable business impact through analytics and AI.

Responsibilities

  • Partner with client Advanced Analytics teams to scope and deliver analytics and AI solutions that solve business problems and generate measurable business value.
  • Deliver projects across marketing mix modelling, promotion effectiveness, ROI analysis, portfolio analytics, segmentation & targeting, omnichannel analytics, Next Best Action (NBA), forecasting, resource optimization and other commercial analytics engagements.
  • Develop analytical and AI solutions supporting pharmaceutical sales, marketing and commercial operations.
  • Stay current with statistical, machine learning, deep learning and Generative AI methodologies to recommend the most appropriate analytical approaches.
  • Develop AI/GenAI POCs, reusable accelerators and standardized analytics frameworks.
  • Lead multiple projects independently while managing small teams of Analysts/Senior Analysts to deliver high-quality solutions.
  • Ensure timely delivery with strong focus on quality, client satisfaction and agreed SLAs.
  • Drive structured project execution through effective planning, documentation and stakeholder communication.
  • Explore emerging AI, GenAI and advanced analytics techniques to enhance business decision-making.
  • Drive automation using reusable code, AI-assisted workflows and scalable analytics solutions.
  • Maintain knowledge repositories, reusable assets, SOPs and quality frameworks to improve delivery efficiency.
  • Build new analytical capabilities, identify business opportunities and support organizational growth.
  • Contribute to whitepapers, capability building, internal assets and thought leadership initiatives.
  • Develop and deliver presentations and recommendations to senior client stakeholders during delivery and business development.
  • Support recruitment, onboarding, mentoring and knowledge-sharing initiatives across the team.
  • Ensure compliance with organizational processes, governance and quality standards.

Skills

Python
PySpark
Machine Learning
Deep Learning
NLP
Generative AI
LLMs
Omnichannel Analytics

Education

B.Tech / Masters in Computer Science or related quantitative field

Tools

Azure
AWS
GCP
Docker
Git
Tableau
Power BI
Qlik

Job description

Overview

We are looking for a seasoned in Advanced Analytics for the Lifesciences/Pharma domain. The person will lead a dynamic team focused on delivering AI-driven analytics solutions across Marketing, Sales, Medical and Commercial Operations. Proficiency in Machine Learning, Deep Learning, NLP, Generative AI, Large Language Models (LLMs), Commercial and Omnichannel Analytics and Python/PySpark is essential.

Roles and Responsibilities
  • Partner with client Advanced Analytics teams to identify, scope and deliver analytics and AI solutions that solve business problems and generate measurable business value.
  • Deliver projects across marketing mix modelling, promotion effectiveness, ROI analysis, portfolio analytics, segmentation & targeting, omnichannel analytics, Next Best Action (NBA), forecasting, resource optimization and other commercial analytics engagements.
  • Develop analytical and AI solutions supporting pharmaceutical sales, marketing and commercial operations.
  • Stay current with statistical, machine learning, deep learning and Generative AI methodologies to recommend the most appropriate analytical approaches.
  • Develop AI/GenAI Proof of Concepts (POCs), reusable accelerators and standardized analytics frameworks.
  • Lead multiple projects independently while managing small teams of Analysts/Senior Analysts to deliver high-quality solutions.
  • Ensure timely delivery with strong focus on quality, client satisfaction and agreed SLAs.
  • Drive structured project execution through effective planning, documentation and stakeholder communication.
  • Explore emerging AI, GenAI and advanced analytics techniques to enhance business decision-making.
  • Drive automation using reusable code, AI-assisted workflows and scalable analytics solutions.
  • Maintain knowledge repositories, reusable assets, SOPs and quality frameworks to improve delivery efficiency.
  • Build new analytical capabilities, identify business opportunities and support organizational growth.
  • Contribute to whitepapers, capability building, internal assets and thought leadership initiatives.
  • Develop and deliver presentations and recommendations to senior client stakeholders during delivery and business development.
  • Support recruitment, onboarding, mentoring and knowledge-sharing initiatives across the team.
  • Ensure compliance with organizational processes, governance and quality standards.
Additional Information
  • Strong interpersonal and client communication skills.
  • Excellent leadership, collaboration and stakeholder management abilities.
  • Strong analytical thinking and problem-solving mindset.
  • Storyboarding and storytelling skills to translate analytics into business insights.
  • Ability to manage multiple priorities in a matrix organization.
  • Passion for continuous learning, innovation and adoption of emerging AI technologies.
  • Strong commitment to quality, ownership and customer success.
Eligibility Criteria
Required Experience
  • 4-10 years of experience in Advanced Analytics, Data Science or AI.
  • 2-4 years of experience in Healthcare, Lifesciences or Pharmaceutical Analytics is preferred.
  • Strong quantitative, analytical and problem-solving skills.
  • Ability to quickly understand new datasets and translate them into business insights.
  • Experience working with global teams and cross-functional stakeholders is desirable.
  • Proven ability to deliver measurable business impact through analytics and AI.
Technical Skills
  • Proficient in Python, PySpark or R for machine learning and statistical modeling with exposure to SQL; SAS or Alteryx is an added advantage.
  • Expertise in Regression, Classification, Clustering, Bayesian Models, Time Series, NLP, Feature Engineering, Recommendation Systems and Generative AI techniques.
  • Experience building and deploying Deep Learning models including CNN, RNN, LSTM and Transformer architectures.
  • Experience in Omnichannel Analytics including Marketing Mix Modelling, Next Best Action, customer segmentation, campaign optimisation and Pharma CRM analytics.
  • Hands-on experience with NLP, semantic search, chatbots, document summarisation, question answering and information extraction.
  • Proficient in GPT, Claude, Gemini, Llama, LangChain, LlamaIndex, Prompt Engineering and Retrieval-Augmented Generation (RAG).
  • Hands-on experience with Azure, AWS or GCP along with Python, Docker, Git and deployment of scalable AI applications.
  • Experience with visualization tools such as Tableau, Power BI or Qlik.
  • Strong project management, documentation and presentation skills.
  • Pharmaceutical commercial analytics knowledge is highly desirable.
Good to Have Skills
  • Exposure to Databricks, Spark, Hadoop, Hive, Feature Stores, Vector Databases, MLOps/LLMOps and Responsible AI practices.
  • Knowledge of optimisation techniques, stochastic models, Markov Chains and Multi-Touch Attribution.
Basic Qualifications

B.Tech/Masters (or equivalent) in Computer Science, Statistics, Applied Mathematics, Data Science, Bioinformatics, Operations Research, Econometrics, Economics or related quantitati

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