Requirements: English
Company: Exsolv
Region: brussels region, belgium , Brussels
About Exsolv:
Exsolv is a Brussels-based consultancy at the forefront of Data and Artificial Intelligence innovation. We specialize in providing expert Consultancy, Audit, and Solution Development services to empower our partners in overcoming unique challenges. Our holistic approach fosters collaboration across diverse domains, including Data Science, Advanced Analytics, and Artificial Intelligence.
At Exsolv, our "Solvers" are passionate professionals equipped with cutting-edge tools, a culture of continuous learning, and an unwavering commitment to delivering high-impact solutions.
We are seeking a Data Science & Machine Learning Specialist with a proven ability to design, develop, and deploy transformative AI and machine learning solutions.
Your Role:
As a Data Science & Machine Learning Specialist, you will work alongside multidisciplinary teams to unlock the full potential of data assets for clients. You will design state-of-the-art ML models, develop data-driven insights, and deploy production-grade AI solutions. Leveraging your expertise, you will help clients overcome their most pressing challenges and create sustainable value using AI and ML.
What Were Looking For:
Required Skills and Qualifications
- Educational Background: Bachelors or Masters degree in Data Science, Artificial Intelligence, Computer Science, or a related field.
- Languages: Written & Spoken Fluency in English AND French or Dutch
- Seniority: 3-7 years of work experience
- Programming Skills: Expertise in Python and SQL, with experience in big data tools like Apache Spark or Databricks.
- Machine Learning Mastery: Proficiency in TensorFlow, PyTorch, and scikit-learn for designing, training, and deploying ML models.
- Cloud Expertise: Hands-on experience with Azure Machine Learning, AWS SageMaker, or GCP Vertex AI for scalable AI deployments.
- Data Visualization: Proficiency in tools like Tableau, Power BI, and Python-based libraries such as Matplotlib, Seaborn, and Plotly.
- Statistics and Mathematics: Deep understanding of linear algebra, calculus, probability, and advanced statistical techniques.
- Soft Skills: Exceptional communication, critical thinking, and stakeholder management skills.
Preferred Skills
- Familiarity with advanced ML techniques, such as reinforcement learning, graph ML, and large language models (LLMs).
- Experience with MLOps tools like MLflow, Kubeflow, and Docker/Kubernetes.
- Knowledge of causal inference frameworks (e.g., DoWhy, EconML) and time-series forecasting methods.
- Certifications such as Microsoft Certified: Azure AI Engineer Associate, AWS Certified Machine Learning, or Google Professional ML Engineer.
What Youll Do:
Core Expertise
- Client Engagement: Collaborate with clients to identify data challenges, define objectives, and recommend AI/ML solutions that align with business goals.
- Model Development: Design and train advanced machine learning models using frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Insight Generation: Transform complex datasets into actionable insights using statistical analysis and advanced visualization tools like Power BI or Tableau.
Technical Implementation
- Machine Learning Solutions: Develop models for classification, regression, clustering, and NLP using modern techniques, including deep learning and reinforcement learning.
- Data Engineering: Collaborate with Data Engineers to build robust data pipelines and optimize data for ML applications using platforms like Azure, AWS, or GCP.
- MLOps: Deploy and maintain models in production environments using MLOps pipelines with tools like MLflow or Kubeflow.
- Cloud Deployment: Implement AI workflows on cloud platforms such as Azure Machine Learning, AWS SageMaker, or GCP Vertex AI with scalability and performance in mind.
Research and Innovation
- Stay updated on advancements in AI/ML technologies and incorporate state-of-the-art practices into client projects.
- Explore innovative methodologies like transfer learning, Vision Transformers, and graph neural networks to enhance solutions.
Project Management
- Lead end-to-end ML projects, from probl