Alekh Bansal

Work History

Assistant Manager -Data Analytics

Motive Inc.

09.2023 - Current

Led the design, development, and launch of the Tier-1 Manager Dashboard to address support leaders' need for improved visibility into team KPIs and better accountability. To meet this requirement, created a centralized dashboard solution that streamlined performance management and made team metrics easily accessible. Collaborated with cross-functional teams to incorporate feedback and ensure the dashboard met user needs, resulting in daily adoption by over 30 support leaders. This initiative enhanced KPI visibility by 100%, improved decision-making, and received positive feedback from at least five cross-functional stakeholders
Resolved $12.8 million in credit statement discrepancies impacting monthly business reporting by identifying and reconciling data inconsistencies across Salesforce, Zuora, and Snowflake. To ensure reliable and unified reporting, built three Tableau dashboards that consolidated data from Salesforce, Zuora, and Snowflake. These efforts restored data integrity, eliminated conflicting reports, and empowered leadership to make data-driven decisions with confidence
Automated and enhanced reporting across departments by leading a team of 3 data analysts to address high manual effort and inconsistency in existing operations processes. Streamlined and automated more than 15 dashboards and reporting tools for the Implementation, Support, and Operations teams, collaborating closely with these groups while troubleshooting pipeline issues and aligning business logic as needed. These initiatives reduced manual reporting time by 50%, improved analytics accuracy, and increased operational efficiency for over 100 users.

Senior Data Analyst

Bharti Airtel Limited

04.2021 - 09.2023

Built predictive models to optimize engineer appointment slots by addressing inefficiencies in daily allocation that were impacting task completion rates. To tackle this, I identified key variables influencing slot availability and developed multiple linear regression and Random Forest models using historical operational data. This approach resulted in a model mean absolute error (MAE) of 40%, and led to a 15% increase in the daily number of tasks completed per engineer during Q4 2022
Enabled data-driven VoLTE and VoWiFi adoption campaigns by partnering with the marketing team to drive increased usage among Airtel customers who are not currently using these features. Leveraged k-means clustering to segment users based on their 4G data usage, and created targeted cohorts for the campaign. As a result, VoLTE and VoWiFi user adoption increased by 15% in 2022.
Analyzed and improved the Appointment Journey feature for Airtel Works by evaluating its performance after launch. Utilized R and PostgreSQL to analyze user and slot allocation data, generating insights on feature effectiveness and automation opportunities. These insights led the HDO Head to enforce automated slot changes, resulting in a 70% increase in automated slot allocations.

Data Science Analyst

Accenture Strategy & Consulting

03.2019 - 04.2021

Developed advanced time series forecasting models for site occupancy by addressing the need for precise expansion planning among clients. Built and fine-tuned over 15 different ARIMA, ARIMAX, and ETS models, achieving a mean absolute error (MAE) of 30% to reliably forecast site occupancy trends. As a result, clients were able to open new locations proactively whenever projected occupancy exceeded 80%, allowing for more effective and timely business expansion.
Enhanced sales incentive accuracy through in-depth marketing data analytics after clients raised concerns about irregularities in sales representative detailing activities. Took the initiative to analyze more than 100 million rows of multichannel marketing data using SQL, R, and Tableau, identifying patterns of suspicious activity and inefficiencies. This deep-dive analysis empowered clients to accurately calculate incentive compensation for sales reps, ensuring fairness, and promoting compliance.
Designed interactive dashboards to drive adoption of Interactive Visual Aids (IVA) by pharmaceutical reps across global markets. Created over 10 IVA dashboards integrating multichannel marketing data for regions including the US, EU, and LATAM, with a focus on engaging and actionable visualization. These dashboards contributed to a 15% year-on-year increase in the number of reps actively using IVA, supporting more effective and measurable marketing strategies.

Data Scientist

Impact Data Analysis Private Limited

07.2017 - 03.2019

Developed a jewelry recommendation system as part of a two-member team to address client needs for more effective cross-selling campaign planning. Collaborated on the end-to-end design and deployment of the tool, which analyzed customer purchase patterns to make personalized product recommendations. As a result, the system enabled clients to run targeted campaigns, leading to a 6.2% year-over-year increase in units per transaction (UPT) at client-owned stores.
Built an inventory forecasting model for a Canadian jewelry organization that was encountering losses due to inventory shortages. Led the development and deployment of an advanced forecasting framework in Python, generating over 240,000 ARIMA, ARIMAX, and ETS time series models to predict product-level inventory needs. This initiative helped the client reduce inventory-related losses by 15.4% in Q1 of 2018.
Developed multiple user dashboards to visualize and track the business impact of both the recommendation and inventory models. Designed dashboards that provided actionable insights for stakeholders, enabling more informed decisions, and allowing users to monitor campaign effectiveness and inventory trends in real time.

Trainee Decision Scientist

Mu Sigma Business Solutions private Limited

09.2015 - 05.2017

Processed large-scale patient-level healthcare data by addressing the challenge of extracting insights from over 100 million rows of EHR and EMR data, combined with survey data. Utilized advanced SQL queries to aggregate and analyze the information, and built intuitive Tableau dashboards to visualize key patterns. These dashboards empowered clients to evaluate underlying causes for drug switching among patients, and to assess the occurrence of potential adverse drug events.
Optimized patient data retrieval processes by identifying slow query performance in Teradata as a bottleneck for timely analytics. Employed optimization techniques such as primary partition indexing (PPI) and efficient integer-to-integer matching to streamline the extraction of patient-level data. As a result, reduced backend query times by 80% and improved Tableau dashboard responsiveness by 40%, significantly enhancing the user experience for clients performing real-time data analysis.

Summary

Overview

Work History

Assistant Manager -Data Analytics

Senior Data Analyst

Data Science Analyst

Data Scientist

Trainee Decision Scientist

Education

Master in Financial Engineering - Financial Engineering

B.E in Civil And Environmental Engineering - Civil Engineering

Higher Secondary (XII), CBSE -

Secondary Education (Class X) -

Skills

Certification

Languages

Interests

Timeline

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