Senior Data Scientist
NEORIS
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This role on the market
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What scientist roles keep asking for: Python (48%), Machine learning (37%), SQL (22%), C++ (18%), Java (17%), Deep learning (14%), R (13%), LLMs (13%) — counted across their open postings here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for scientist roles keep coming back to Python, Machine learning, SQL, C++. Practise those questions before you sit with NEORIS.
Questions you are likely to be asked
- Why do you want to join NEORIS?
- What is your experience with Machine learning? Tell me one thing you learned the hard way.
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
- Tell me about a time the data was messy or wrong. What did you do?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Senior Data Scientist at NEORIS interview free →NEORIS is a Digital accelerator that helps companies enter the future, having 20 years of experience as Digital Partners of some of the largest companies in the world. We have more than 4,000 professionals in 11 countries, with our multicultural startup culture where we cultivate innovation, continuous learning to create high-value solutions for our clients.
We are seeking a highly experienced Senior Data Scientist with strong expertise in advanced analytics, statistical modeling, machine learning, and Generative AI to help drive data-driven decision-making across the organization. This role requires a hands-on professional capable of analyzing complex datasets, developing predictive models, and building AI-powered solutions that deliver measurable business impact.
The ideal candidate combines deep Data Science expertise with practical experience in Machine Learning and GenAI applications, collaborating closely with cross-functional teams to design, deploy, and scale intelligent solutions in production environments.
Key Responsibilities
🔹 Advanced Analytics & Data Science
• Design and develop statistical models and advanced analytical solutions to solve complex business problems.
• Perform exploratory data analysis (EDA), feature engineering, and hypothesis testing on large and diverse datasets.
• Apply machine learning techniques such as regression, classification, clustering, forecasting, and anomaly detection.
🔹 Machine Learning & AI Solutions
• Build, train, evaluate, and optimize machine learning models for production and business applications.
• Develop and support Generative AI solutions, including applications leveraging LLMs, embeddings, prompt engineering, and RAG-based architectures.
• Support deployment and monitoring of ML and AI models in collaboration with engineering and MLOps teams.
🔹 Data Engineering & Visualization
• Work with structured and unstructured data sources to prepare datasets for analysis and modeling.
• Develop dashboards, visualizations, and reports to communicate insights effectively to stakeholders.
• Collaborate with data engineers to improve data pipelines and analytical workflows.
🔹 Business Collaboration
• Partner with business stakeholders to understand requirements and identify opportunities for data-driven improvements.
• Translate technical findings into actionable insights and strategic recommendations.
• Support decision-making through data storytelling and executive-level presentations.
🔹 Innovation & Best Practices
• Stay current with emerging trends in Data Science, AI, Machine Learning, and Generative AI.
• Promote best practices in experimentation, reproducibility, documentation, and model governance.
• Mentor junior team members and contribute to technical knowledge sharing.
Required Qualifications
• 7+ years of experience in Data Science, Advanced Analytics, or Machine Learning roles.
• Strong proficiency in Python and SQL for data analysis and model development.
• Hands-on experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or XGBoost.
• Practical experience designing or implementing Generative AI solutions, including: Large Language Models (LLMs), Prompt engineering, Embeddings and semantic search, Retrieval-Augmented Generation (RAG)
• Strong background in: Statistical analysis, Predictive modeling, Feature engineering, Model evaluation and optimization.
• Experience working with large datasets and cloud-based analytics environments.
• Familiarity with ML deployment concepts and collaboration with engineering teams.
• Experience with data visualization tools such as Tableau, Power BI, or similar.
• Strong communication skills with the ability to explain technical concepts to non-technical stakeholders.
• English – Advanced (required).
Preferred Qualifications
• Experience with cloud platforms such as GCP, AWS, or Azure.
• Familiarity with MLOps concepts, CI/CD pipelines, Docker, Kubernetes, or MLflow.
• Experience with Computer Vision or advanced AI use cases.
• Background in industries such as supply chain and retail.
Come and meet us on: http://www.neoris.com, on Facebook, LinkedIn, Twitter, or Instagram @NEORIS.
Marina Molina
#LI-MM3
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Listed on greenhouse · posted 2026-05-18. ApplySarthi collects openings and links to application pages; the role is advertised by NEORIS, not by us.