Lead Data Scientist

About Tarento: Tarento is a fast-growing technology consulting company headquartered in Stockholm, with a strong presence in India and clients across the globe. We specialize in digital transformation, product engineering, and enterprise solutions, working across diverse industries including retail, manufacturing, and healthcare.

Our teams combine Nordic values with Indian expertise to deliver innovative, scalable, and high-impact solutions. We're proud to be recognized as a Great Place to Work , a testament to our inclusive culture, strong leadership, and commitment to employee well-being and growth. At Tarento, you’ll be part of a collaborative environment where ideas are valued, learning is continuous, and careers are built on passion and purpose.

Below skill are mandatory:

• Large Language Models (LLMs) Classical Machine Learning (Supervised & Unsupervised Learning) Generative AI Python Microsoft Azure Azure Data Factory & Azure Data Foundry Azure, Azure DevOps, Azure Machine Learning, Azure Databricks, Azure Data Factory, Azure AI Foundry, Azure AI Vision (OCR, Custom Vision, Face). Your main responsibilities will include Design, develop, and deploy predictive models including forecasting, classification, regression, and segmentation Build and customize deep learning NLP models, multimodal models (text + vision), and context‑aware AI solutions. Implement and tune custom loss functions, advanced quantitative methods, and high‑impact ML algorithms. Deep knowledge of statistical modelling, experimentation, and advance data analysis. Conduct rigorous model validation, diagnostics, and performance monitoring. Perform complex statistical analyses and generate meaningful insights that influence business strategy. Work closely with product managers, engineering teams, and business leaders to define analytical requirements. Conduct A/B testing, causal inference, and optimization modelling (linear, mixed‑integer, multi‑objective). Translate ambiguous business needs into clear analytical frameworks and modelling approaches. Define and track KPIs and product metrics, supporting data driven prioritization and roadmaps. Exposure to agentic AI workflows leveraging LLMs, retrieval, tool use, and reasoning systems. You have the needed skills and qualities to work in analytics, including: Strong proficiency in Python (Pandas, Num. Py, Scikit‑learn; Tensor. Flow/Py. Torch preferred). Expertise in SQL, relational databases, data warehouses. Hands‑on experience with Databricks, large‑scale analytics, and ML workflows. Deep knowledge of statistical modeling, experimentation, and causal analysis. Experience working with Azure cloud services. The following skills are considered distinct advantages: Work with large‑scale datasets including 1 TB+ data processing for analytics and modeling tasks. Build, optimize, and maintain data pipelines using Databricks, MLflow, and cloud‑native tooling. Develop data engineering scripts (e.g., parsers, transformers) required for ML dataset preparation. Integrate, clean, preprocess, and validate data from multiple sources ensuring governance, accuracy, and compliance Certification from Microsoft:
• Azure AI Fundamentals AZ‑900 Azure Fundamentals AI‑900 Azure AI Engineer Associate Certification (AI-102)