Senior Data Scientist

Akkodis; Wallonië; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Akkodis seeks a Senior Data Scientist to join a team operating at the intersection of data, human behavior, and advanced analytics. You will leverage large datasets to uncover behavioral patterns and generate actionable insights using advanced statistical, ML, and AI techniques to create real business value.

You will collaborate with engineering, technical, and business stakeholders to ensure findings are relevant and explainable, delivering results that drive practical outcomes across complex,

Qualifications

• Master's degree or PhD in Data Science, Statistics, CS, Mathematics, Engineering, or related quantitative discipline.
• Approximately 4–8 years of hands-on experience in Data Science, Advanced Analytics, ML or Applied AI.
• Strong proficiency in Python for data analysis, ML, experimentation, and rapid prototyping.
• Solid knowledge of statistics, ML, and AI techniques including feature engineering, model validation, dimensionality reduction, predictive modeling.
• Ability to work independently, structure analytical approaches, and challenge assumptions when results are unclear.
• 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 to explain complex concepts clearly to diverse audiences.

Responsabilités

• 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 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 such as clustering, dimensionality reduction, factor analysis, and various ML models.
• Conduct proofs-of-concept to rapidly assess applicability and value of new methodologies.
• Review literature and best practices to identify innovative approaches for 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 and actionable.
• Present insights, recommendations, assumptions, and limitations clearly to technical and non-technical audiences.

Connaissances

Python

Statistics

Machine Learning

Data Analysis

Feature Engineering

Communication

Formation

Master's degree or PhD in Data Science or related quantitative field

Outils

SQL

Snowflake

Databricks

Description du poste

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.