Job description:

About HCLTech
HCLTech is a global technology company, spread across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. We re powered by our people a global, diverse, multi-generational talent - representing 161 nationalities whose unique spark, perspective and boundless passion drive our culture of proactive value creation and problem-solving.
Our purpose is to bring together the best of technology and our people to supercharge progress for everyone, everywhere our clients, partners, their stakeholders, communities, and the planet. As a company, we are deeply focused on accelerating our ESG agenda. We are also creating technology-enabled sustainable solutions with and for our clients and partners. We embed ESG imperatives into every aspect of our business and ensure that the progress we supercharge is responsible, inclusive and beneficial to all our stakeholders in the long term. We have committed to achieving net zero by 2040.

To learn more about how we can supercharge progress for you, visit www.hcltech.com

Senior Data Science Specialist

Job Summary
To lead the development of advanced data science solutions, drive innovation in AI and machine learning, and leverage data-driven insights to optimize business strategies and decision-making.

• Key Responsibilities
  1. Lead the design and deployment of advanced machine learning models, AI solutions, and predictive analytics.
  2. Develop and refine complex algorithms for large-scale data processing, feature engineering, and pattern recognition.
  3. Conduct deep exploratory data analysis, visualization, and statistical modeling to extract actionable insights.
  4. Partner with business and technology leaders to integrate data-driven solutions into enterprise strategies.
  5. Implement deep learning, natural language processing, and big data technologies to enhance analytics capabilities.
  6. Drive data governance, model interpretability, and ethical AI practices for responsible data science implementation.
  7. Optimize, automate, and scale data science pipelines for improved operational efficiency and impact.
  8. Mentor junior data scientists, foster a data-driven culture, and stay ahead of emerging trends in AI and analytics.