Senior Data Scientist
Il y a 2 heures
Namur, Wallonia, Belgique
Akkodis
Temps plein
Gratuit avec email ou Google
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Gratuit avec email ou Google
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.
All potential applicants are encouraged to scroll through and read the complete job description before applying.
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. xlxgzvr
- Flexible and collaborative working culture.
All potential applicants are encouraged to scroll through and read the complete job description before applying.
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. xlxgzvr
- Flexible and collaborative working culture.