Data Scientist Engineer

Job Description

We are looking for a Data Science Specialist to join our 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 data-centric improvements that enhance machine learning performance.

Requirements

• Master's or PhD degree in Data Science, Computer Science, Applied Mathematics, Statistics, Physics, or a related field
• 2+ years of hands-on experience working with machine learning datasets
• Experience with time-series, sensor, image, or video data
• Strong Python skills and experience with NumPy, pandas, matplotlib, and seaborn
• Experience with dimensionality reduction and representation analysis techniques such as UMAP, t-SNE, and PCA
• Solid understanding of machine learning fundamentals, model evaluation, and diagnostics
• Experience supporting both traditional machine learning and deep learning projects

Nice to Have

• Experience working with sensor data, including radar, magnetic, environmental, 3D, or IoT datasets
• Familiarity with scikit-learn preprocessing workflows
• Experience handling imbalanced datasets, noisy labels, sensor noise, and data drift
• Knowledge of model interpretability, feature importance, and embedding analysis
• Experience working with data annotation and labeling teams
• Familiarity with MLflow, Weights & Biases, DVC, or similar tools

Responsibilities

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

This is an excellent opportunity to work on challenging machine learning problems where data quality and analysis directly impact product success and model performance.

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 health insurance from the first days, regardless of the probationary period.The Gift from the Company - Christmas holidays from December 25 to December 31.Cooperation 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.