Consultant, Global Analytics

Job Location: Manyata Tech Park, Bangalore

Work Mode: Hybrid

Work Shift Timings: Gen Shift (11:00 AM to 8:00 PM)

Preferred Skills:

6+ years of experience in Data Science with a strong foundation in Python, machine learning libraries and Generative AI models.

Hands-on experience in designing, developing, and testing applications using Generative AI for tasks like text summarization, text categorization, content creation, and question answering.

Collaborate with stakeholders to understand business needs and translate them into innovative data-driven solutions, exploring the power of Generative AI to create novel approaches.

Leverage expertise in Python, Machine Learning (ML), and cloud platforms (Microsoft Azure) to tackle complex problems involving structured and unstructured data, including text data.

Acquire data from primary or secondary sources and maintain databases/data systems.

Develop and implement data science solutions using Python and Azure Machine Learning services, integrating Generative AI models where applicable.

Develop and deploy user-facing applications using frameworks like Django, Flask, or Streamlit to visualize and interact with data science solutions, machine learning models, and Generative AI functionalities.

Good to have:

Contribute to the implementation of ML/LLM Ops practices for model deployment and management, ensuring continuous improvement and monitoring of machine learning models and Generative AI solutions.

Continuously research and recommend advancements in ML and Generative AI to improve team productivity, model performance, and overall data strategy.

Possess excellent communication skills to effectively collaborate with cross-functional teams and translate complex technical concepts into clear and actionable insights.

Full-Stack Development Lifecycle: Collaborate with the manager throughout the project lifecycle to design, develop, test, deploy, and maintain data-driven applications using machine learning models and Generative AI.

Data Acquisition and Management: Collaborate with data engineers and stakeholders to identify and acquire relevant data sources and assist in data cleaning, transformation, and preparation for analysis and ensure continuous data flow for analysis and model training.

Data Exploration & Analysis: Perform exploratory data analysis (EDA), create data visualizations, and conduct statistical analysis to support model development and decision-making.

ML & Generative AI Development: Build, train, evaluate, and deploy machine learning models and Generative AI models using Python and Azure Machine Learning services.

Communication & Reporting: Generate reports and present findings on data analysis and the potential of Generative AI solutions.

Stakeholder Engagement & Communication: Interact with stakeholders throughout the project lifecycle to gather requirements, present analysis findings, explain machine learning models and Generative AI recommendations, and ensure effective communication across technical and non-technical audiences.

Technology Exploration & Innovation: Evaluate emerging datasets, technologies (e.g., new Generative AI techniques), and tools that can potentially enhance the analytical platform and future data-driven solutions.