Data Science Associate

As a Data Science Associate at Metyis, you will be responsible for executing data science projects from start to end. Your key responsibilities will include: - Understanding client business problems, defining analytical approaches, and developing actionable solutions. - Engaging directly with stakeholders to gather requirements, present findings, and guide data-driven decisions. - Preprocessing and analyzing structured and unstructured data using statistical approaches. - Building and deploying predictive models, forecasting solutions, and recommendation systems. - Collaborating with engineering, product, and business teams to translate insights into outcomes. - Communicating results clearly through presentations and storytelling. To qualify for this role, you should have: - Graduate degree or higher with courses in programming, econometrics/data science. - 3-6 years of professional work experience in the advanced analytics domain, using statistical modeling and deep learning for business problem solutions. - Well-developed logical reasoning, critical thinking, and problem-solving abilities. - Excellent presentation 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. It would be good to have experience with: - Generative AI 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).,