Data Scientist II leveraging advanced statistical methods and machine learning at F5. Join the Data & Insights team to create impactful data products and drive business success.
About the role
- Associate Data Scientist at Kyndryl's AI Innovation Hub transforming raw data into actionable insights. Collaborating with senior scientists to develop machine learning models and tackle real business challenges.
Responsibilities
- Collaborate with senior scientists and engineers to develop and validate machine learning and predictive models
- Participate in the end-to-end model lifecycle — from data collection and preparation to training, evaluation, and documentation
- Contribute to feature engineering, exploratory analysis, and performance optimization of models
- Apply statistical and analytical techniques to extract meaningful patterns and insights from data
- Assist in model deployment and monitoring within MLOps environments and cloud platforms
- Document experiments and ensure transparency, reproducibility, and traceability of results
- Stay up to date with new algorithms, frameworks, and best practices in data science and applied AI
- Actively contribute to a collaborative, knowledge-sharing culture within the Hub
Requirements
- 2–4 years of experience in data science, advanced analytics, or machine learning projects
- Practical experience building and validating models for classification, regression, or segmentation tasks
- Solid skills in Python and core data science libraries (Pandas, NumPy, Scikit-learn, Matplotlib, XGBoost, LightGBM)
- Familiarity with neural networks and deep learning frameworks (TensorFlow, PyTorch)
- Strong understanding of data preprocessing, handling missing values, unbalanced datasets, and outlier detection
- Experience with model evaluation and validation (ROC, AUC, F1, RMSE, precision, recall, cross-validation)
- Basic knowledge of cloud AI platforms (Azure ML, Vertex AI, SageMaker, Databricks)
- Awareness of model versioning and experiment tracking tools (MLflow, DVC)
- Understanding of Responsible AI concepts — bias mitigation, transparency, and interpretability
- Bachelor’s degree in Computer Engineering, Mathematics, Statistics, Physics, Data Science, or related field
- Postgraduate or Master’s degree in Artificial Intelligence, Machine Learning, or Data Analytics is valued
- Complementary training or certifications in Machine Learning, Data Science, or MLOps are a plus
Benefits
- Flexible, supportive environment prioritizing well-being
- Dynamic, hybrid-friendly culture that supports your growth
- Be Well programs designed to support health and well-being
- Access to cutting-edge learning opportunities from major tech companies
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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