Lead Data Scientist, Full Stack

INMANBP Bangalore (INMANBP) Manyatha

Kyndryl

At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day.

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Who We Are

At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. So why work at Kyndryl? We are always moving forward – always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities.


The Role

Join Kyndryl, the world’s largest technical services company, with 80,000 employees operating in over 60 countries and serving 75% of the Fortune 100 to modernize and manage the world’s mission-critical systems. Kyndryl provides advisory, implementation, and managed services to de-risk and support digital transformations.

Our mission is to leverage the skills inherent in our technical and consultative workforce to drive impactful results for our clients. We seek to optimize the development and deployment of our employees’ skills while providing an industry-leading experience for both our Kyndryls and clients. Kyndryl is one of the Top 100 Global Most Loved Workplaces®, and as a cutting-edge services company, we know that our people are our success.

Kyndryl is a global, largely remote company, where you’ll join a group of 40 People and Workforce Analytics professionals, including business translators, data scientists, analysts, and developers. You will engage with senior leadership, diverse HR professionals, fellow data scientists, data engineers, and analysts, as well as business leaders to ensure our insights are scientifically rigorous and aligned with business goals. Your work will directly influence our enterprise strategy, operations, and workforce, impacting tens of thousands of employees.

As a Full-Stack Lead Data Scientist, you will bring a diverse skill set across data collection, analysis, model development, and deployment. You will collaborate closely with the data engineer and data scientist to develop predictive models, implement machine learning algorithms, and deploy end-to-end solutions that optimize our workforce strategies.

This role demands proficiency across the full data science lifecycle, from data wrangling to delivering insights via advanced visualizations.

Responsibilities include:

  • End-to-End Data Science Solutions: Build, deploy, and maintain full-stack data science solutions, from data extraction to machine learning model deployment and monitoring.
  • Collaboration with Data Engineering and Science: Partner with the data engineer and data scientist to ensure clean, structured data is available for analysis and predictive modeling. Participate in designing scalable data pipelines and architectures to support analytical and machine learning workflows.
  • Machine Learning Model Development: Design and implement advanced machine learning models, including regression, classification, and clustering techniques, to predict workforce needs and identify skills gaps.
  • API Development and Integration: Develop APIs to integrate machine learning models into enterprise applications and workflows, enabling real-time decision-making.
  • Data Management: Ensure data integrity, consistency, and accuracy across multiple platforms, working closely with data governance teams to align processes.
  • Advanced Data Visualization: Use data visualization tools (e.g., Tableau, Power BI) to translate complex analytical insights into actionable business recommendations for HR, business leaders, and other stakeholders.
  • Optimization Models: Implement optimization algorithms to recommend actions such as hiring, training, or workforce engagement based on model outputs and business constraints.
  • Performance Monitoring and Improvement: Continuously track model performance and refine processes for model efficiency and scalability.

Your Future at Kyndryl

Every position at Kyndryl offers an opportunity to grow your career. We provide hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or specialize, you can find your opportunity here.


Who You Are

Who You Are

You’re good at what you do and possess the required experience to prove it. However, equally as important – you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused – someone who prioritizes customer success in their work. And finally, you’re open and borderless – naturally inclusive in how you work with others.

To be successful in this role you will have the following required skills and expertise:

  • Bachelor's degree in Data Science, Computer Science, Statistics, or a related field.
  • 3-5 years of experience as a data scientist with a focus on full-stack data science, including model building, deployment, and API development.
  • Proficiency in Python, R, or similar languages for statistical modeling and machine learning.
  • Experience with big data platforms (e.g., Hadoop, Spark) and cloud services (AWS, Azure, GCP).
  • Strong SQL skills and familiarity with both relational and NoSQL databases.
  • Expertise in building and deploying machine learning models (e.g., TensorFlow, PyTorch).
  • Experience with data visualization tools such as Power BI, Tableau, or similar.
  • Familiarity with RESTful APIs and integrating machine learning models into business applications.
  • Strong understanding of optimization algorithms, data architecture, and performance monitoring.
  • Excellent communication skills to translate technical findings into actionable business insights.

Preferred Skills

  • Master’s in Data Science, Computer Science, Statistics, or a related field.
  • Familiarity with workforce analytics, HR data, and related systems.
  • Knowledge of graph databases (e.g., Neo4j, GraphQL) is a plus.


Being You

Diversity is a whole lot more than what we look like or where we come from, it’s how we think and who we are. We welcome people of all cultures, backgrounds, and experiences. But we’re not doing it single-handily: Our Kyndryl Inclusion Networks are only one of many ways we create a workplace where all Kyndryls can find and provide support and advice. This dedication to welcoming everyone into our company means that Kyndryl gives you – and everyone next to you – the ability to bring your whole self to work, individually and collectively, and support the activation of our equitable culture. That’s the Kyndryl Way.


What You Can Expect

With state-of-the-art resources and Fortune 100 clients, every day is an opportunity to innovate, build new capabilities, new relationships, new processes, and new value. Kyndryl cares about your well-being and prides itself on offering benefits that give you choice, reflect the diversity of our employees and support you and your family through the moments that matter – wherever you are in your life journey. Our employee learning programs give you access to the best learning in the industry to receive certifications, including Microsoft, Google, Amazon, Skillsoft, and many more. Through our company-wide volunteering and giving platform, you can donate, start fundraisers, volunteer, and search over 2 million non-profit organizations.  At Kyndryl, we invest heavily in you, we want you to succeed so that together, we will all succeed.

Get Referred!

If you know someone that works at Kyndryl, when asked ‘How Did You Hear About Us’ during the application process, select ‘Employee Referral’ and enter your contact's Kyndryl email address.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: API Development APIs Architecture AWS Azure Big Data Classification Clustering Computer Science Data governance Data management Data pipelines Data visualization Engineering GCP GraphQL Hadoop Machine Learning ML models Model deployment Neo4j NoSQL Pipelines Power BI Predictive modeling Python PyTorch R Spark SQL Statistical modeling Statistics Tableau TensorFlow

Perks/benefits: Career development

Region: Asia/Pacific
Country: India

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