Data Scientist

What you’ll do:

• Scoping, driving, and delivering complex projects across multiple teams.

• Work with product/business owners, enterprise/application/solution architects, data scientists, engineers, and other stakeholders to scale up Big Data and data science research and development initiatives w.r.t to the industrial standards.

• Develop deterministic and machine learning models (ML) and pilot projects to find the most scalable solution to business problems (plug and play on readymade ML models and python abilities).

• He/she should be a self-starter who has a strong interest in dealing with statistics, understanding complex systems, solving challenging challenges, and organizing and presenting data and reports.

• Identifies the data needed for root cause analysis, gathers, and pulls data, analyses it to create a hypothesis, and uses data to validate it.

• Develops and maintains scalable predictive models and drive insights that can be of value to the business. • Implement Continuous Integration/Continuous Deployment (CI/CD) pipelines for machine learning models.

• Demonstrate technical expertise and provide guidance to business stakeholders on how to gain value from the data science initiatives.

• Leverage and plug and play deep learning frameworks (e.g., TensorFlow, PyTorch) to build and optimize neural networks for various applications.

• Create, create, and apply cutting-edge AI models and algorithms to resolve challenging business issues and keep up with the most recent developments in AI research and use creative approaches in practical situations.

• Understanding of conceptual, logical, and physical architectures for cloud-based data solutions – AWS preferred.

• Provide complete frameworks and solutions for projects. Keep an eye on and measure efficacy Establish best practices and frameworks for various data and analytics landscape capabilities.

• Creates and assesses commercial and open-source data lineage tools.

• Familiarity with the logical, conceptual, and physical architectures of cloud-based data solutions; preference is given to AWS.

• Create frameworks and comprehensive solutions for these kinds of tasks. Keep an eye on and measure efficacy Establish best practices and frameworks for various data and analytics landscape capabilities.

• Creates and assesses commercial and open-source data lineage tools.

• Works closely with all business units and engineering teams to develop strategy for consumption of insights

• Document the processes and maintain code repositories in GitHub Requirements. Requirements /

Key Performance Areas:

Technical Skills:

• At least 3-5 years of data science experience

• Experience with Python(preferred), Shell Scripting and/or R and SQL

• Experience working with a data pipeline in the public cloud (AWS highly preferred).

• Research and prototype novel GenAI solutions aligned with business goals

• Work with cross-functional teams to translate requirements into AI capabilities

• Experience in leveraging Agentic AI in Workflows

• Data Visualization: Seaborn or Matplotlib (Python)

• Source control knowledge: GitHub

• Agile / Scrum experience preferred

• Knowledge in SQL & Big Data analytics.

• Experience in any ticketing tool preferably JIRA Domain

Requirements:

• Provide technical expertise and guidance to support the integration of generative AI solutions.

• Experience in o eCommerce and/or Retail o Fintech is preferred

• In-depth understanding of statistical and predictive techniques like regression, classification, and forecasting

• Knowledge of techniques such as but not limited to Linear and Logistic regression, Random Forest, Boosting and Bagging techniques, SVM, Clustering and time series forecasting.

• Strong Knowledge in Statistical Modelling, Machine learning, Deep learning & AI.

• Strong Knowledge in Data Science tools and techniques.

Soft Skills:

• Familiarity with data visualization tools and excellent story telling skills.

• Critical thinking and implementation in relevant use-cases

• Strong interpersonal and management skills.

• Excellent verbal and written communication skills.

• Excellent Data Story telling skills.

• To be able to work in a fast-paced agile development environment

• Ideation and Conceptualization of existing business problems and implement the same.

• Knowledge in Project/Program Management. Academic

Requirements:

• Bachelor’s degree in (Computer Science / Data Science