Overview
Overview
We are seeking a highly skilled and experienced Senior Data Science Engineer to join our "Data & AI" service line at CBTW. In this role, you will play a critical role in designing, implementing, and deploying advanced data science and machine learning solutions for our European clients. You will work at the intersection of data engineering, machine learning, and software engineering to deliver scalable, production-ready AI solutions.
You will lead end-to-end data science projects, from problem definition and data exploration to model development, deployment, and monitoring. You will collaborate with cross-functional teams including data engineers, software engineers, and business stakeholders to create innovative AI-driven solutions that deliver measurable business value. As a senior member of the team, you will also mentor junior data scientists and drive best practices in MLOps and model lifecycle management.
Responsibilities
Key Responsibilities
- Data Science and Machine Learning
Design and develop advanced machine learning models for various use cases including predictive analytics, recommendation systems, natural language processing, and computer visionConduct thorough data exploration and analysis to identify patterns, trends, and insightsImplement feature engineering and selection techniques to optimize model performanceEnsure model interpretability and explainability for business stakeholders- MLOps and Model Deployment
Design and implement end-to-end MLOps pipelines for model training, validation, and deploymentEstablish automated model monitoring and retraining workflowsImplement A/B testing frameworks for model performance evaluationEnsure models meet production requirements for scalability, latency, and reliability- Data Engineering and Infrastructure
Collaborate with data engineers to design and optimize data pipelines for ML workloadsImplement data quality validation and monitoring systemsWork with cloud platforms (AWS, Azure, GCP) to deploy scalable ML infrastructureUtilize big data technologies (Spark, Kafka, etc.) for large-scale data processing- Solution Architecture and Design
Design scalable and robust data science solutions that align with business requirementsArchitect real-time and batch inference systems for production deploymentImplement best practices for model versioning, experiment tracking, and reproducibilityEnsure solutions follow security and compliance requirements- Leadership and Collaboration
Lead cross-functional project teams including data scientists, engineers, and business stakeholdersMentor junior data scientists and promote knowledge sharing within the teamCollaborate with clients to understand business requirements and translate them into technical solutionsDrive innovation and adoption of new tools, techniques, and methodologies
Qualifications
Required Skills and Experience
Technical Skills
Machine Learning: Deep expertise in supervised and unsupervised learning, deep learning frameworks (TensorFlow, PyTorch), and model optimization techniquesProgramming: Strong proficiency in Python and/or R, with experience in SQL and knowledge of additional languages (Java, Scala) as a plusData Engineering: Experience with data pipeline tools (Airflow, Prefect), big data technologies (Spark, Kafka), and data warehousing conceptsMLOps: Hands-on experience with MLOps tools (MLflow, Kubeflow, Sagemaker) and model deployment strategies (Docker, Kubernetes)Cloud Platforms: Proficiency with cloud-based ML services (AWS SageMaker, Azure ML) and infrastructure managementStatistical Analysis: Strong foundation in statistics, experimental design, and hypothesis testingAgentic AI: Interest or experience with agentic Artificial intelligence frameworks and multi-agent systems (LangChain, AutoGen, CrewAI, etc.) is a plusExperience
Minimum of 5 years of experience in data science and machine learning, with at least 2 years in a senior or lead roleProven track record of deploying machine learning models in production environmentsExperience with end-to-end data science project delivery in enterprise environmentsStrong understanding of software development best practices and agile methodologiesSoft Skills
Excellent communication skills, both written and verbalFluent in French and English (required)Able to travel in Europe for client engagements and project deliveryStrong problem-solving abilities and analytical mindsetAbility to translate complex technical concepts for business stakeholdersLeadership experience with cross-functional teamsPreferred Qualifications
Advanced degree (Master's or PhD) in Data Science, Computer Science, Statistics, or related fieldExperience with specific industry domains (finance, healthcare, retail, etc.)Knowledge/experience with Databricks, Azure Fabric, or IBM Watson X (a plus)Publications in peer-reviewed conferences or journalsCertifications in cloud platforms (AWS Certified Machine Learning, Azure Data Scientist Associate, etc.)
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