Senior Data Scientist

We are seeking a highly skilled Senior Data Scientist to join an innovative team working at the intersection of data, human behavior, and advanced analytics.

In this role, you will leverage large-scale sensor, operational, and customer-related datasets to uncover meaningful behavioral patterns and generate actionable insights. You will apply advanced statistical, machine learning, and AI techniques to solve complex real-world challenges, transforming raw data into practical and explainable business value.

This is an exciting opportunity for a curious and autonomous professional who enjoys combining analytical rigor, applied research, and stakeholder collaboration to drive impactful results.

Key Responsibilities

• Analyze large and complex datasets from connected systems, operational environments, and customer feedback sources.
• Design and develop interpretable features and behavioral dimensions to identify patterns, trends, and user profiles.
• Combine multiple data sources, including structured and unstructured data, to generate richer insights and predictive capabilities.
• Evaluate, compare, and validate analytical approaches suchas:
• Clustering
• Dimensionality reduction
• Factor analysis
• Correlation analysis
• Supervised and unsupervised machine learning models
• Conduct proof-of-concept studies to rapidly assess the applicability and value of new methodologies.
• Review scientific literature and industry best practices to identify innovative approaches that can be adapted to business challenges.
• Validate model performance, robustness, reliability, and limitations using sound statistical practices.
• Collaborate with engineering, technical, and business stakeholders to ensure findings are relevant, actionable, and aligned with operational realities.
• Present insights, recommendations, assumptions, and limitations clearly to technical and non-technical audiences.

Required Qualifications

• Master's degree or PhD in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative discipline.
• Approximately 4-8 years of hands‑on experience in Data Science, Advanced Analytics, Machine Learning, or Applied AI.
• Strong expertise in Python for data analysis, machine learning, experimentation, and rapid prototyping.
• Solid knowledge of statistics, machine learning, and AI techniques, including: Feature engineering
• Model validation
• Dimensionality reduction
• Predictive modeling
• Pattern discovery
• Ability to work independently, structure analytical approaches, and challenge assumptions when results are unclear or inconclusive.
• Experience applying analytical methods to complex, real-world datasets rather than solely relying on standard modeling pipelines.
• Strong critical thinking and problem‑solving capabilities.
• Excellent communication skills with the ability to explain complex concepts in a clear and accessible way.
• Business‑oriented mindset with a focus on delivering practical and explainable outcomes.

Nice to Have

• Experience working with connected systems, IoT, sensor, mobility, industrial, or operational data.
• Exposure to customer analytics, behavioral analysis, survey data, persona development, or user experience analytics.
• Experience with modern data platforms and technologies such as:
• SQL
• Snowflake
• Databricks Similar cloud-based analytics environments
• Knowledge of Large Language Models (LLMs), Generative AI, or AI‑assisted analytics.
• Experience in interdisciplinary environments combining data science, engineering, and product development.

What We Offer

• The opportunity to solve complex, high‑impact challenges using advanced analytics and AI.
• A collaborative environment where innovation, experimentation, and continuous learning are encouraged.
• Exposure to cutting‑edge technologies, methodologies, and real‑world applications.
• Professional growth opportunities within a dynamic and forward‑thinking organization.
• Competitive compensation and benefits package.
• Flexible and collaborative working culture.