Joel Jacob

Operations Associate

Bengaluru, Karnataka, India9 yrs 10 mos experience

Most Likely To Switch

Key Highlights

8 years of experience in data-driven business solutions.
Expert in data modeling and analytics in Edtech and Retail.
Proven track record in leading analytics teams.

Stackforce AI infers this person is a Data Analytics professional with expertise in Healthcare and Edtech sectors.

Contact

Skills

Core Skills

Data AnalyticsBusiness AnalyticsMarketing AnalyticsOperations Analytics

Other Skills

Data MappingData WarehousingRStatistical AnalysisArena Simulation SoftwareSoftware as a Service (SaaS)Microsoft Power QueryProduct StrategyKey Performance IndicatorsKey MetricsBusiness InsightsStrategy ConsultingBusiness StrategyPython (Programming Language)A/B Testing

About

Analytics professional with 8 years of experience in driving data-based business solutions, data modeling, process modeling and data integration projects in Edtech and Retail domains

Experience

9 yrs 10 mos

Total Experience

1 yr 11 mos

Average Tenure

2 yrs 2 mos

Current Experience

Onepay

Ops Analyst

Apr 2024 – Present · 2 yrs 2 mos · Hybrid

Skill-lync

Senior Manager Analytics

Jun 2022 – Aug 2023 · 1 yr 2 mos · On-site

Set up and led the Centralized Analytics team

Data MappingData WarehousingData AnalyticsBusiness Analytics

Vedantu

Lead Business Analyst

Apr 2021 – May 2022 · 1 yr 1 mo · Bangalore Urban, Karnataka, India

Led the Marketing Analytics team

Data MappingData WarehousingMarketing AnalyticsBusiness Analytics

Simplilearn

2 roles

Manager - Analytics

Promoted

Jun 2020 – Jan 2021 · 7 mos

Data MappingData WarehousingData AnalyticsBusiness Analytics

Business Analyst - Data Science

Oct 2018 – Jun 2020 · 1 yr 8 mos

Data MappingData WarehousingData AnalyticsBusiness Analytics

Mu sigma inc.

Decision Scientist

Jun 2015 – Aug 2018 · 3 yrs 2 mos · Bengaluru Area, India

Lead a team supporting operations analytics for the pharmacy business of a Fortune 10 company
Projects
Developed a predictive model in R using logistic regression, which estimates the likelihood of customers coming back to pick up their orders in the pharmacy. The model optimizes the usage of workforce in prescription processing by de-prioritizing orders with a high likelihood of not getting picked up. The model reduced the drug return to stock % across 4000+ pharmacies by an average of 30%.
Helped develop a base stock model for 'intermittent demand' pharmacy items (96% of total items)
Developed a discrete event simulation model in Arena, which simulated the Rx fulfillment processes in the pharmacy and checked for impacts in workforce, and total processing time in optimizing the conventional processes

Data MappingData WarehousingOperations AnalyticsData Analytics