Maninder Singh

Experienced analytics professional with expertise across FMCG, AI-data services and technology environment, bridging data, research, and product teams to optimize model performance and user engagement. Adept at solving complex analytics challenges across engagement and operational efficiency.

Lead Data Annotation - AI & Data Analytics at ZZAZZ (2024-04 – 2026-04)

• Improved Click-Through Rate (CTR) by 8% within 2 months by identifying growth opportunities across high-impression articles and recommending optimal publishing times and placements using SQL and Databricks.
• Increased average reader time spent by 5% in 4 weeks by performing audience segmentation based on scroll depth and session duration, building Tableau dashboards to guide editorial teams.
• Reduced reporting time by 80% by building automated reporting pipelines for daily content data crawls and replacing manual reports, flagging data discrepancies in real-time, and improving data quality monitoring using Python and MongoDB.
• Improved AI pricing model accuracy by contributing to an article-to-event matching pipeline processing 10K-18K daily articles; achieved 78% Recall@1 and 95% Recall@5 using DistilBERT and cosine similarity text embeddings.
• Guided editorial and onboarding strategy by conducting Exploratory Data Analysis on session duration, scroll depth, and bounce rates using SQL, presenting actionable retention insights directly to leadership teams.
• Recognized by product and content teams for effectively translating complex event datasets into clear, actionable business use-cases and metrics, significantly improving stakeholder decision-making.

Data Analyst at Shaip.AI Data (2021-09 – 2024-02)

• Analyzed large-scale NLP training datasets to identify data quality gaps, edge-case distributions, and reviewer decision inconsistencies impacting model performance, improving classification accuracy by 10% through data-driven guideline optimization using Dataloop.
• Improved team productivity by 20% by developing interactive Excel dashboards to track daily accuracy rates, quality agreement, and task throughput; empowered managers with real-time visibility to address performance bottlenecks before they impacted client SLAs.
• Improved operational efficiency by managing and querying 2M+ records in SQL Server to build automated weekly performance reports, presenting quality insights to Fortune 100 clients to ensure strict adherence to project timelines.
• Optimized QA workflows and reduced data inconsistencies by conducting targeted performance reviews on outlier data points, sharing actionable feedback with operational teams to streamline the data collection process.

Bachelor of Engineering in ECE – Punjab Technical University (2014-07 – 2018-06)