Senior Data Scientist

Company Name : Willware Technologies

Experience : 10+ Years

Location : Bangalore

Work Mode : Onsite

Role : Senior Data Scientist

Roles and Responsibilities

Important Key words:-

• Large Language Models (LLMs)
• Classical Machine Learning (Supervised & Unsupervised Learning)
• Generative AI
• Python
• Microsoft Azure
• Azure Data Factory & Azure Data Foundry

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 contextaware AI solutions.
• Implement and tune custom loss functions, advanced quantitative methods, and highimpact ML algorithms.
• Deep knowledge of statistical modeling, 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 modeling (linear, mixedinteger, multiobjective).
• Translate ambiguous business needs into clear analytical frameworks and modeling 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, NumPy, Scikitlearn; TensorFlow/PyTorch preferred).
• Expertise in SQL, relational databases, data warehouses.
• Handson experience with Databricks, largescale 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 largescale datasets including 1 TB+ data processing for analytics and modeling tasks.
• Build, optimize, and maintain data pipelines using Databricks, MLflow, and cloudnative 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