Data Scientist

Role & responsibilities

• Execute data science projects from start to end.
• Understand client business problems, define analytical approaches, and develop actionable solutions.
• Engage directly with stakeholders to gather requirements, present findings, and guide data-driven decisions.
• Preprocess and analyze structured and unstructured data using statistical approach.
• Build and deploy predictive models, forecasting solutions, recommendation systems.
• Collaborate with engineering, product, and business teams to translate insights into outcomes.
• Communicate results clearly through presentations and storytelling.

Preferred candidate profile

• Graduate degree or higher with courses in programming, econometrics / data science
• Experience: 3 - 8 years of relevant professional work experience in advanced analytics domain, using statistical modeling and deep learning for business problem solutions.
• Well-developed Logical Reasoning, Critical Thinking & Problem-Solving abilities.
• Excellent presentations skills and storytelling capabilities.
• Self-driven with a collaborative attitude and a passion for delivering business value through data.
• Strong hands-on experience in Python/R and SQL.
• Good understanding and Experience with cloud platforms such as Azure, AWS, or GCP.
• Experience with data visualization tools in python like Seaborn, Plotly. Good understanding of Git concepts.
• Good experience with data manipulation tools in python like Pandas, Numpy.
• Must have worked with scikit learn, NLTK, Spacy, transformers.
• Strong foundation in machine learning algorithms, predictive modeling, and statistical analysis.
• Good understanding of deep learning concepts, especially in NLP and Computer Vision applications.
• Proficiency in time-series forecasting and business analytics for functions like marketing, sales, operations, and CRM. Exposure to tools like Mlflow, model deployment, API integration, and CI/CD pipelines.

Good to have:

• Generative AI Experience with text and Image data.
• Familiarity with LLM frameworks such as LangChain and hubs like Hugging Face.
• Exposure to vector databases (e.g., FAISS, Pinecone, Weaviate) for semantic search or retrieval-augmented generation (RAG).

In a changing world, diversity and inclusion are core values for team well-being and performance. At Metyis, we want to welcome and retain all talents, regardless of gender, age, origin or sexual orientation, and irrespective of whether or not they are living with a disability, as each of them has their own experience and identity.