Data Scientist (ML/Pandas/NumPy/IoT, Ukraine)

Your Project

We are looking for a Data Science Specialist to join a product-focused engineering team. In this role, you will work closely with data scientists, ML engineers, and domain experts to analyze complex datasets, understand model behavior, and drive improvements through data quality, structure, and insight-driven analysis. This position is highly hands-on and focuses on improving model performance through deep data understanding.

Your Role

Data Understanding and Representation Analysis
- Analyze high-dimensional sensor and feature datasets using UMAP, t-SNE, PCA, and similar techniques
- Identify clusters, anomalies, blind spots, distribution gaps, and class or environment mismatches
- Diagnose dataset shift, domain drift, sparsity, and representation collapse

Model-Aware Data Analysis
- Perform data analysis aligned with classical ML models including XGBoost, SVR, k-NN, and tree-based models
- Support analysis for deep learning models such as CNNs and Transformers
- Analyze embeddings, confusion matrices, and model failure patterns to trace errors back to data issues

Data Quality and Curation
- Investigate imbalanced data, noisy sensor signals, mislabeled samples, and ambiguous cases
- Develop approaches for improving weakly labeled or unlabeled data including clustering and pseudo-labeling
- Perform data mining on large collections of field data to extract insights and patterns
- Design processes for converting noisy or partially verified data into high-quality validated datasets

Insight-Driven Improvements
- Translate exploratory findings into clear recommendations for data filtering, relabeling, or new data collection
- Advocate for and implement data-centric improvements to enhance model robustness
- Work closely with engineering teams to integrate improved data workflows into ML pipelines

Your Profile

• Master’s or PhD in Data Science, Computer Science, Applied Mathematics, Statistics, Physics, or a related field
• 2–3+ years of hands-on data science experience with real-world ML datasets including time-series, images, video, or sensor data
• Strong proficiency in Python and core data science libraries such as NumPy, pandas, matplotlib, seaborn
• Experience using dimensionality reduction and representation analysis tools such as UMAP, t-SNE, PCA
• Experience analyzing data for classical ML and deep learning pipelines
• Strong understanding of ML fundamentals, evaluation methods, and diagnostic techniques

Preferred Qualifications

• Experience with sensor or time-series data such as magnetic, radar, 3D, environmental, or IoT data
• Familiarity with scikit-learn preprocessing workflows
• Experience handling imbalanced datasets, label noise, sensor noise, and data drift
• Understanding of embedding analysis, feature importance, and model interpretability methods
• Experience working with data annotation teams or managing labeling processes
• Familiarity with MLOps or data versioning tools such as MLflow, Weights and Biases, or DVC

What You Will Love About Working Here

• We care about all our employees and want them to feel as comfortable as possible. That's why we offer them health insurance from the first days, regardless of the probationary period.
• The gift from the company - Christmas holidays from 25 December to 31 December.
• Сooperation with Superhumans center and Veteran HUB. Capgemini Engineering has supported the launch of psychological rehabilitation department of Superhumans. Our team also donated over UAH 500 000 prosthetics for three Ukrainian defenders. Currently, we support psychological counseling provided by the Veteran Hub, and we have implemented an internal policy making the company friendly to military and veterans with the assistance of the Hub.