Ranjan Kumar
New York,NY
Summary
Experienced and Dynamic Data Analytics Leader with 7+ years of cross-industry experience, leading and inspiring teams of data scientists, consultants & data engineers to deliver transformative data-driven solutions for business growth and success.
Overview
7
7
years of professional experience
Work History
Analytics Senior Manager
EXL Service
06.2021 - Current
- Led comprehensive workstreams for a leading US Sports League client, analyzing linear TV and digital game viewership to understand live game consumption trends, predict viewership (TV/OTT), optimize league schedules and refine marketing strategy
- Developed a sophisticated ML-powered MMM & MTA for ad budget optimization, mitigating user bias & achieving a 25% increase in ROAS
- Successfully strategized the marketing budget to implement an Omni-channel strategy, resulting in a 30% increase in revenue and improved brand health through enhanced customer engagement and targeted campaigns
- Regularly present to CXO/VP-level stakeholders, on data-backed business strategy and product conception & potential opportunities
- Addressed client's challenges tactically and strategically through root cause analysis, structuring analytical solutions, and presenting it
- Managed RFP responses and supervise the execution of successful pilot projects and POCs across various client engagements
- Developed and maintained automated IGV Nielsen dashboards using SQL, Python, and Power BI, reducing report generation time by 40%
- Engineered data pipelines for data ingestion, preprocessing, and feature extraction using Python, PySpark and SQL, reducing data preparation time by 65% to use in model building directly.
- Developed and maintained a Streamlit MMM optimizer dashboard, leveraging MMM results to swiftly optimize marketing budgets, reducing decision-making time from days to few hours
- Developed multiple predictive ensemble regression models to forecast Linear TV and OTT viewership, enabling proactive measures to mitigate significant drops and address underperforming viewership factors effectively with test accuracy of 88.6%.
Analytics Senior Consultant
Accenture Analytics
06.2017 - 05.2021
- Prepared an automated end to end Market Mix Modeling (MMM) framework for major telecom client which can build ~1000 models using innovative ML and Statistical Models in Python & R in a few hours; reducing overall project delivery timelines by 60%
- Achieved ~ 20% increase in marketing ROI for major telecom client through advanced MMM modeling using BBN and optimization
- Utilized statistical techniques to perform hypothesis testing, A/B testing, and regression analysis to support data-driven decision-making
- Engineered and deployed multiple Interactive R Shiny dashboard for dynamic media budget optimization and automated base variable creation, which reduced manual efforts by 60% and 50% respectively.
- Mentored, upskilled, and trained team members in building ML automation workflows across departments.
Education
B.S - M.S Dual Degree - Mathematics And Scientific Computing
Indian Institute of Technology Kanpur
Uttar Pradesh, India05.2017
Skills
- Python PySpark R SQL
- Artificial Intelligence Machine Learning
- Power BI Streamlit R Shiny
- Data Structure Data Analytics
- Strategic Planning Business Planning
- Cross-Functional Collaboration
- Data-driven decision-making
- Project Management Team Building
- Stakeholders Management
- Marketing Analytics
- Industry Expertise: Sports, Telecom, Retail/CPG, Banking
Languages
English
Full Professional
Hindi
Native or Bilingual
Work Availability
monday
tuesday
wednesday
thursday
friday
saturday
sunday
morning
afternoon
evening
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Timeline
Analytics Senior Manager
EXL Service
06.2021 - Current
Analytics Senior Consultant
Accenture Analytics
06.2017 - 05.2021
B.S - M.S Dual Degree - Mathematics And Scientific Computing
Indian Institute of Technology Kanpur
Accomplishments
- 🏆 The People Manager Award - Recognized for exceptional leadership and team management skills at EXL.
- 🏆 “Customer Centricity” Spot Award - Awarded for outstanding dedication to customer satisfaction and service at EXL.
- Supervise team of 8-10 Data Analysts & Consultants, ensuring that all project deliverables and insights are delivered accurately and in a timely manner.
Key Academic Projects
Multi-Class Classification of Objects in Video Using Artificial Intelligence
May 2016 – August 2016
- Developed a system to detect and classify objects in videos, distinguishing between pedestrians and various types of vehicles (2-wheelers, 3-wheelers, 4-wheelers).
- Implemented Histogram of Oriented Gradients (HOG) feature extraction on grayscale images, maintaining the aspect ratio of resized images.
- Applied various machine learning algorithms, including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), and tree-based approaches (Random Forest, Extra Trees, AdaBoost, Gradient Boosting Classifier) as well as Deep Neural Networks (DNN).
- Achieved the best accuracy using the AdaBoost algorithm, with 89.1% on training data and 71.45% on test data.
Portfolio Optimization Using Clustering
January 2015 – April 2015
- Optimized a portfolio based on risk factors by clustering stock data from 70 BSE 100 companies with K-means and spectral clustering.
- Applied the Markowitz algorithm for efficient portfolio creation.
Summer Internship
Machine Learning Based MROI Modelling (BBN)
Accenture India
May 2016 – August 2016
- Developed a machine learning-powered media mix model for a top Australian telecom client, analyzing channel networks for both direct and indirect impacts.
- Applied five different feature selection algorithms, ultimately selecting Recursive Feature Elimination (RFE) based on model fitness, coverage, and runtime.
- Constructed a Bayesian Belief Network (BBN) model using R to assess interactions between marketing activities, sales, and other variables.
- Achieved an R² of 92.1% and a Mean Absolute Percentage Error (MAPE) of 8.99% on test data, with a MAPE of 4.95% on training data.
- Strategized budget allocation and weight distribution for marketing activities, increasing direct contribution to 21.5% from a benchmark of 18%.
Summer Internship
May 2016 – August 2016
Machine Learning Based MROI Modelling (BBN)
Accenture India
- Developed a machine learning-powered media mix model for a top Australian telecom client, analyzing channel networks for both direct and indirect impacts.
- Applied five different feature selection algorithms, ultimately selecting Recursive Feature Elimination (RFE) based on model fitness, coverage, and runtime.
- Constructed a Bayesian Belief Network (BBN) model using R to assess interactions between marketing activities, sales, and other variables.
- Achieved an R² of 92.1% and a Mean Absolute Percentage Error (MAPE) of 8.99% on test data, with a MAPE of 4.95% on training data.
- Strategized budget allocation and weight distribution for marketing activities, increasing direct contribution to 21.5% from a benchmark of 18%.
Key Academic Projects
Multi-Class Classification of Objects in Video Using Artificial Intelligence
May 2016 – August 2016
- Developed a system to detect and classify objects in videos, distinguishing between pedestrians and various types of vehicles (2-wheelers, 3-wheelers, 4-wheelers).
- Applied various machine learning algorithms, including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), and tree-based approaches (Random Forest, Extra Trees, AdaBoost, Gradient Boosting Classifier) as well as Deep Neural Networks (DNN).
- Achieved the best accuracy using the AdaBoost algorithm, with 91.1% on training data and 84.52% on test data.
Portfolio Optimization Using Clustering
January 2015 – April 2015
- Optimized a portfolio based on risk factors by clustering stock data from 70 BSE 100 companies with K-means and spectral clustering.
- Applied the Markowitz algorithm for efficient portfolio creation.
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