Mayank Mishra

• Set up end-to-end data and analytics for new post-order screen launch; drive data instrumentation for front-end app/product and backend events to create/analyze product funnel (CTR, CVR), onboarding, and engagement user journey on post-order screen.

• Create/automate 7+ analytics-backed business frameworks: measuring user quality (repeat and retention) for partnership with Amazon and Flipkart.

• Build multiple linear regression model for predicting redemption of money voucher coupons.

• Collaborate with multiple stakeholders across product/engineering/PMO/leadership/Business; ability to push back, raise red flags, prompt in communication, manage priorities amongst ongoing requests/projects.

• Lead/mentor 5 analysts to embed a data-driven culture; train 40+ folks on SQL, MS Excel, and various analytical frameworks.

• Take L&D sessions for 50+ analytics teams on interview guidelines.

• Automate Complex RCAs, impact measurement from campaigns/offers, multiple dashboards, and WBR/MBR reports; design schemas and create fact/base tables for org-wide usage.

• Devise new metrics called Intent to Cancel and average response time metric for business.

• Part of core hiring team for analytics, creating interview guidelines doc for BA/SBA/Manager and training for it to ensure high adherence in interview process.

• Worked extensively on creating data pipelines via Airflow, Python, and complex database queries in SQL.

• Created data pipeline and goals dashboard using Tableau from scratch for Sales OPS team.

• Automate a lot of various manual tasks on Google Sheets via Python scripts.

• Created automated dashboards on Apache superset via Presto SQL for stakeholders.

• Monitored A/B testing and experiments to measure impact of changes and initiatives.

• Performed feature engineering, and exploratory data analysis including descriptive analysis in Python.

• Built Market KPI and business performance dashboard using Tableau.

• Developed rule-based Model to identify OOS rules and Mathematical equations for maximizing volume.

• Feature selection via Stepwise Regression and Random Forest model, using Log-Log regression model for sales prediction.

• Performed feature engineering, and exploratory data analysis including descriptive analysis in Python.

• Worked on data segmentation using K-means clustering techniques in Python.

• Automated 90% of ad-hoc daily reporting using Python and Tableau tools by creating user-friendly dashboard and automated email camping through Oracle responses (RI) tool.

• Formulated solutions and dashboards utilizing Tableau Suite of products from Tableau Desktop to Tableau Server.

• Identified opportunities to automate and convert raw data into intelligent dashboards for optimal decision-making.

• Worked closely and collaboratively with businesses to understand requirements and translate them into Tableau views.

• Conducted Ad-hoc & Restricted data reporting, including providing support for ad-hoc requests and special projects as assigned the handling of assigned and periodic reports needed to be published weekly/bi-monthly/monthly/quarterly.