Oct 2023 – Aug 2025 · 1 yr 10 mos · Stafford, England, United Kingdom · Hybrid

• Collaborate with backend, frontend, and product management teams for seamless ML/AI feature integration.
• Utilise Azure Bicep and Pulumi for infrastructure provisioning as Infrastructure-as-Code (IaC), automating MLOps workflows on Azure.
• Designed and implemented comprehensive machine learning and artificial intelligence features for Ascend, including Anomaly Detection, Forecasting, and an AI Assistant, significantly reducing development and deployment time by 70%.
• Assumed leadership of the entire ML and AI practice following the departure of the previous manager, ensuring seamless continuity and strategic direction.
• Pioneered the development and deployment of the first AI assistant for the ASCEND platform using LangGraph, Large Language Models (LLMs), and agentic frameworks, empowering users to query their data and extract actionable insights. Deployed on Azure and integrated with the frontend via FastAPI.
• Engineered advanced memory capabilities, including short-term and long-term memory, enabling the AI assistant to perform tool calling and retrieve user-specific data efficiently.
• Designed APIs to deliver streaming responses for chat completions and standard responses for chat history retrieval, enhancing user experience and system responsiveness.
• Optimised chat history storage in a cloud SQL database using strategic update and insert operations, ensuring seamless session data management.
• Implemented a summarisation node to condense long conversation threads, reducing token consumption and accelerating response times.
• Delivered analytical overview feature that identifies significant correlations between multiple metrics and provides a detailed daily breakdown, exportable as a .csv file—addressing a critical gap in the platform’s functionality.
• Designed and implemented AWS Glue ETL jobs for extracting and transforming semi-structured bidding provider log data into readable structured data for deep predictive analytics.

Jun 2023 – Sep 2023 · 3 mos · Leeds, England, United Kingdom · Hybrid

Sep 2022 – Sep 2023 · 1 yr · Leeds, England, United Kingdom

Dec 2020 – Aug 2022 · 1 yr 8 mos · Hyderabad, Telangana, India

• Used Pandas Dataframe and Dask in Python to join multiple datasets, data cleaning, data pre-processing, exploratory data analysis, statistical analysis and unsupervised learning for consumer profiling.
• Demonstrated expertise in Microsoft Azure, ETL, Big Data and Data Warehousing to design, implement and manage PySpark data pipelines for strategic customer targeting in the North America region using the client's customer purchase data consisting of more than 100 Million records.
• These pipelines were utilised to push out new campaigns and prescription reminders to customers, allowing the client to reach out to target consumers more easily and quickly.
• Worked on analysing the requirements, data mapping, implementation using Git, Azure Databricks, Apache Airflow, PyCharm, unit testing, used acceptance testing and documentation of multiple medical campaigns and medical products.
• Used Azure Databricks, PyCharm and Apache Airflow to work with data consisting of hundreds of millions of data points, to create complex data pipelines for customer targeting and to transform it into actionable data that is used by downstream systems to reach out to targeted consumers via email or SMS channels.
• Utilised Apache Airflow for orchestrating automated data pipelines and for analysing, troubleshooting and implementation of new enhancements to existing data pipelines.
• Using Azure Databricks and PySpark, I helped a US-based pharmaceutical firm with their COVID vaccination data for the North America region by designing and automating data transformation pipelines to refresh and populate daily reports. These reports aided top-level management in making informed decisions by allowing them to examine vaccination rates across the United States.
• Used Azure Synapse Analytics to design, implement and test a plug-and-play data governance and monitoring framework using Azure Synapse.

Oct 2019 – Nov 2020 · 1 yr 1 mo · Hyderabad Area, India

• Used Azure Machine Learning Service SDKs and Python to deploy an LSTM algorithm as a container instance to Azure cloud.
• Utilised Azure Data Factory for orchestration to build complex hourly automated jobs to refresh reporting data.
• I used Azure MLOps for model versioning, continuous integration, and continuous deployment of new model versions using Azure DevOps and Azure ML.
• I leveraged Azure data services like ADF, ADLS Gen2, Azure Databricks, Azure SQL, Azure ML, AAS and Azure DevOps to cater to client data needs and to built efficient analytics solutions.
• Designed and implemented an ELTL pipeline on Microsoft Azure to extract data from multiple sources like SAP, on premise SQL databases, Oracle databases and staged the raw data as parquet files in Azure Data Lake. Azure Data Factory was utilised for orchestration, while Azure Databricks was used for transforming the raw data into final data and storing it in an Azure SQL data warehouse for futher analytics and reporting.
• Demonstrated success in designing and building advanced data solutions using Azure cloud services like Azure Data Factory (ADF), Azure Databricks, Azure SQL and Azure Analysis Service (AAS) to implement complex automated data pipelines Databricks, Azure SQL and Azure Analysis Service (AAS) to implement complex automated data pipelines for data warehousing, descriptive analytics, machine learning and data visualisations.
• I used reporting tools like Tableau and Power BI to create reports and dashboards.
• Used Azure SQL stored procedures, triggers, tables, functions, views, indexes and constraints to manage client data and to transform it into actionable insights.
• Extensively used Azure Databricks, PySpark and Spark SQL to ingest raw data from Azure Data Lake (acting as a staging layer), transformed it and loaded it into Azure SQL Database for further transformation and analytics.

Oct 2016 – Nov 2018 · 2 yrs 1 mo · Hyderabad Area, India

• I developed SQL queries to access, manipulate, and extract logistics data for downstream BI tasks such as dashboard generation and analytics.
• I was solely responsible for all ASP.NET enhancements and upgrades for one of my client's independent logistics web applications.
• Collaborated with business stakeholders, supply chain managers, finance teams and business analysts to gather requirements for new enhancements on the logistics website.
• Successfully analysed, designed, implemented, tested and deployed new client enhancements to improve the client website's UI, functionality and database management systems.