Senior Data Scientist (Machine Learning)

As a Senior Data Scientist at Kyndryl's AI Innovation Hub, you'll turn complex business challenges into intelligent, data-driven solutions. You'll design, build, and deploy advanced machine learning models that power decision-making and automation for some of the world's leading enterprises. Your mission will be to translate strategic goals into robust analytical solutions - combining statistical rigor, scientific curiosity, and engineering excellence. Working hand-in-hand with AI architects, data engineers, and functional experts, you'll lead the full model lifecycle - from data preparation and experimentation to validation, deployment, and continuous monitoring. You'll operate in an environment that encourages innovation, collaboration, and applied science, contributing not only to the success of client projects but also to the growth and maturity of Kyndryl's AI ecosystem.

Your Mission

• Design, develop, and validate machine learning models that solve complex business problems through data.
• Translate functional and strategic requirements into predictive, prescriptive, and analytical solutions.
• Lead the end-to-end model lifecycle - from data exploration and feature engineering to deployment and monitoring.
• Collaborate with architects and engineers to ensure seamless integration of models into production environments.
• Apply best practices in MLOps, ensuring models are traceable, reproducible, and governed throughout their lifecycle.
• Evaluate and optimize model performance using robust metrics and explainability techniques.
• Document, communicate, and present insights clearly to both technical and business audiences.
• Mentor junior data scientists, promoting technical excellence, innovation, and a culture of learning within the Hub. Who You Are

• 4+ years of experience developing predictive models and advanced analytics solutions in business contexts.

• Proven expertise across the entire model lifecycle - data preparation, modeling, validation, evaluation, and deployment.

• Strong programming skills in Python and core ML libraries (Pandas, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, StatsModels).

• Solid foundation in statistical analysis, supervised and unsupervised learning, regression, classification, clustering, anomaly detection, and forecasting.

• Experience with feature engineering, data transformation, and data augmentation for model improvement.

• Knowledge of MLOps and CI/CD for models, using tools such as MLflow, DVC, Airflow, Kubeflow, or Vertex Pipelines.

• Skilled in model evaluation and optimization (ROC, AUC, F1, RMSE, SHAP, explainability techniques).

• Familiarity with DataOps principles, APIs, ETL pipelines, and relational or NoSQL databases.

• Understanding of AI governance, privacy, and compliance frameworks (GDPR, Responsible AI). Education & Certifications

• Bachelor's or Master's degree in Computer Engineering, Mathematics, Statistics, Physics, Data Science, or related field.

• Postgraduate studies (Master's or PhD) in Artificial Intelligence, Statistics, or Computational Science are highly valued.

• Complementary training in Applied Data Science or Machine Learning Engineering is a plus.

• Continuous learning mindset and commitment to staying current with advances in ML, MLOps, and applied AI. Preferred Skills

• Experience deploying models on cloud-based ML platforms (Azure ML, Vertex AI, SageMaker, Databricks, OpenShift AI).

• Exposure to deep learning, classical NLP, or time-series modeling.

• Familiarity with automated retraining, model versioning, and drift detection frameworks.

• Practical knowledge of data visualization and business intelligence tools for model interpretation.

• Experience leading or mentoring junior team members in applied data science projects.

• Ability to work in agile, cross-functional teams with shared ownership and accountability.

• Strong focus on explainability, traceability, and responsible AI design. Soft Skills

• Analytical and impact-driven mindset, able to define hypotheses and validate them through experimentation.

• Clear and concise communication, transforming technical findings into actionable insights for business teams.

• Business-oriented problem-solving, understanding functional needs and converting them into data-driven solutions.

• Collaborative leadership, fostering teamwork, mentoring, and continuous knowledge sharing.

• Attention to quality and reproducibility, ensuring every model is robust, auditable, and maintainable.

• Curiosity and lifelong learning attitude, keeping pace with new algorithms, frameworks, and methodologies.

• Adaptability, thriving in dynamic environments that blend research, engineering, and innovation. #AgenticAI

Being YouDiversity 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 ExpectWith 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.