A
Akanksha Wagh
About
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San Francisco, California, United States
Résumé
Jobs
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Data ScientistDatadogAug 2025 - Current (1 year 2 months)• Built scalable time-series anomaly detection and forecasting models for distributed observability metrics, enabling proactive
monitoring across cloud infrastructure and improving detection accuracy and operational reliability.
• Designed advanced experimentation frameworks including holdouts, bandits, and synthetic controls to evaluate product
features and model performance across customer segments.
• Developed large-scale telemetry data pipelines using Python and PySpark, supporting near real-time analytics and reducing
data latency for observability insights.
• Implemented zero-shot anomaly detection techniques across new metrics, reducing onboarding time by 35% and enabling
faster monitoring for newly- Data Scientist – Retail & MarketingCompass GroupFeb 2024 - May 2025 (1 year 4 months)• Built GenAI-powered analytics agent using LLMs to automate KPI tracking, weekly reporting, and business insights generation
across marketing and retail stakeholders.
• Developed customer segmentation and demand forecasting models using clustering and regression techniques, improving
inventory planning efficiency and reducing stock imbalances.
• Applied NLP and sentiment analysis on customer feedback data to identify operational gaps and recommend vendor and
product optimization strategies.
• Designed A/B testing frameworks and campaign measurement strategies, improving campaign effectiveness and increasing
conversion performance across multiple marketing initiatives.
• Implemented market basket anal - Data ScientistTATA MOTORSJan 2023 - Jul 2023 (7 months)• Developed predictive maintenance models using IoT sensor time-series data to forecast equipment failures and improve
production reliability across manufacturing lines.
• Built PySpark ETL pipelines integrating machine telemetry and operational datasets to support real-time monitoring and
predictive analytics initiatives.
• Applied anomaly detection and statistical modeling to identify early failure signals across production systems and reduce
unexpected equipment breakdowns.
• Engineered time-series features and model pipelines improving predictive accuracy and enabling proactive maintenance
planning across multiple plants.
• Created dashboards and monitoring tools for plant managers, improving visi - Data ScientistNykaaJun 2021 - Dec 2022 (1 year 7 months)• Built hybrid recommendation systems combining collaborative filtering and content-based approaches to improve product
personalization across web and mobile platforms.
• Developed feature pipelines using transactional, clickstream, and product metadata to enhance recommendation quality and
capture customer intent.
• Implemented daily retraining pipelines using Spark and cloud infrastructure to maintain recommendation accuracy for
large-scale user traffic.
• Conducted A/B testing and experimentation to evaluate recommendation algorithms, improving click-through rate and
conversion performance.
• Developed cold-start solutions using embeddings and session-based modeling to support new users and product
Education
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- Master of Science in Data ScienceStevens Institute of Technology