Posted:1 hour ago|
Platform:
On-site
Full Time
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 /
• 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
• 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.
• 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
• Bachelor’s degree in (Computer Science / Data Science
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