Jan 2025 – Apr 2026 · 1 yr 3 mos · Newcastle Upon Tyne, England, United Kingdom · Hybrid

• 1️⃣ Machine Learning & Predictive Modeling - Built and optimized scalable ML models using Amazon Redshift and SageMaker, supporting advanced analytics, predictive modeling, and cross-platform data integrations.
• 2️⃣ Experimentation & Statistical Analysis - Designed and executed A/B tests and causal experiments using Python (NumPy, SciPy, statsmodels), R, and SQL, applying hypothesis testing, regression, and ANOVA to measure feature impact, improve user engagement, and guide data-driven product decisions.
• 3️⃣ Data Pipelines & Automation - Designed, automated, and optimized data pipelines and workflows with dbt Cloud, PostgreSQL, Python, Apache Airflow, and AWS (S3, Glue), enabling scalable analytics and powering data-driven dashboards in Power BI.
• 4️⃣ Data Ingestion & Integrations - Developed and managed data ingestion pipelines for third-party platforms such as Amazon and TikTok Shop using REST APIs and OAuth 2.0, implementing data validation and transformation with Python, FastAPI, and AWS Lambda to ensure high-quality, reliable datasets.
• 5️⃣ Data Documentation & Governance - Partnered with cross-functional teams to design and maintain comprehensive data documentation, including data dictionaries, schema definitions, and lineage tracking, ensuring consistent, reliable, and user-friendly access to curated data views.

Oct 2023 – Present · 2 yrs 8 mos · Newcastle Upon Tyne, England, United Kingdom · Hybrid

• Designed interactive dashboards in Power BI and Tableau to track customer acquisition, retention, and sales performance; reduced manual reporting by 60% and enabled stakeholders to monitor KPIs in real-time.
• Produced management information and forecasting reports to support planning and decision-making, using Excel, SQL, and Power BI.
• Built automated ETL pipelines in Python and SQL integrating data from PostgreSQL, Snowflake, and Excel, improving data accessibility, reliability, and analytics efficiency.
• Performed advanced data cleansing and quality checks on datasets exceeding 1M rows, resolving inconsistencies and missing values, resulting in 30% more accurate insights.
• Implemented NLP solutions for customer feedback analysis using Python (NLTK, spaCy, transformers) to categorize sentiment and identify key drivers of satisfaction and complaints.
• Applied time series forecasting with Prophet and ARIMA models to predict seasonal sales trends, informing inventory planning and reducing stockouts by 25%.
• Automated reporting and workflows using Python, Power Automate, and Airflow, allowing weekly performance reports to be generated automatically, saving ~10 hours per week.
• Translated complex data into actionable business insights, presenting recommendations on marketing, pricing optimization, and operational efficiency to clients, improving decision-making speed and accuracy.

Apr 2022 – Jul 2023 · 1 yr 3 mos · Bengaluru, Karnataka, India · On-site

• 1. Led data management strategies supporting operational efficiency and performance monitoring
• 2. Delivered executive-level management information reports using Excel, Access, and SQL
• 3. Monitored performance indicators and provided insight through trend analysis
• 4. Led a team to create and deploy machine learning models using Python, TensorFlow, and Google Cloud to extract and translate textual and geolocation data from images.
• 5. Created dashboards using Tableau to effectively communicate insights and drive technical decisions across multi-disciplinary teams.
• 6. Ensured secure handling of sensitive data in line with data protection policies
• 5. Conducted A/B testing to compare the effectiveness of different reporting methods (manual vs. automated) using Google Optimize, Airtable, Tableau, and Excel, leading to a 70% reduction in manual effort and improved efficiency.

Jan 2021 – Apr 2022 · 1 yr 3 mos · Bengaluru, Karnataka, India · On-site

• 1. Processed and analyzed high-resolution satellite imagery to generate detailed geospatial insights, directly supporting global delivery networks with optimized end-mile connectivity for improved delivery operations.
• 2. Utilized spatial data to identify the most efficient delivery routes, contributing to logistics optimization by minimizing travel distances and reducing overall delivery times, thereby enhancing customer satisfaction for international clients.
• 3. Automated various geospatial processes by creating Python scripts to handle repetitive GIS tasks, significantly boosting workflow efficiency while minimizing manual errors, and allowing for quicker turnaround on project deliverables.
• 4. Automated report generation using Airtable, Python, and advanced Excel macros, streamlining reporting processes for internal teams. This reduced manual intervention by 30%.

Sep 2020 – Dec 2020 · 3 mos · Bengaluru, Karnataka, India · On-site

• Reviewing and validating GIS data from external sources and contractors, ensuring consistency and compatibility with internal systems and improving data accuracy.

Mar 2020 – Sep 2020 · 6 mos · Bengaluru, Karnataka, India

Jan 2016 – Feb 2020 · 4 yrs 1 mo · Bengaluru, Karnataka, India · Hybrid