Senior Data Scientist

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 Scientist

Job Summary
To lead advanced data science initiatives, develop predictive models, and drive data-driven decision-making by extracting meaningful insights from complex datasets, enabling business growth and innovation.

• Key Responsibilities
  1. Develop and deploy machine learning models, predictive analytics, and AI solutions to solve business challenges.
  2. Design and optimize algorithms for data processing, feature engineering, and pattern recognition.
  3. Lead data exploration, mining, and visualization to uncover trends and actionable insights.
  4. Collaborate with cross-functional teams to integrate data science solutions into business strategies.
  5. Drive innovation by leveraging advanced statistical techniques, deep learning, and big data technologies.
  6. Ensure data integrity, governance, and best practices in model development and deployment.
  7. Mentor junior data scientists and promote a data-driven culture within the organization.
  8. Stay ahead of industry trends and emerging technologies to enhance analytical capabilities.