Ishika Arora

Product Manager

Seattle, Washington, United States10 yrs 10 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

5+ years in analytics and modeling.
Expertise in machine learning and data analytics.
Led high-impact projects with MIT collaboration.

Stackforce AI infers this person is a Data Science and Analytics expert with experience in Financial Services and Marketing.

Contact

ishikaarora4@gmail.com LinkedIn

Skills

Core Skills

Product ManagementMachine LearningData Analysis

Other Skills

AJAXApache PigApache SparkBig Data AnalyticsBioinformaticsBusiness StrategyCC++Cascading Style Sheets (CSS)D3.jsData AnalyticsData ScienceFlaskGephiHBase

About

I am an Analytics Manager in BudLab team within Anheuser-Busch InBev (ABInBev), based in Cambridge MA. I have 5+ years of experience in modeling and analytics in the financial services and retail industry. Additionally, I have interned at the Beer Garage Incubator at ABInBev, on video data analytics for marketing research, and built Machine Learning algorithms for event detection and identification in video data. I completed my Masters in Analytics from Georgia Institute of Technology, majoring in Computational Data Analytics. My prior experience in Machine Learning, and coursework at Georgia Tech, give me a strong background in mathematical modeling, data analytics and software development.

Experience

Microsoft

2 roles

Senior Product Manager

Promoted

Jun 2023 – Present · 2 yrs 9 mos · Redmond, Washington, United States

Product ManagementProduct DevelopmentProduct Marketing

Product Manager 2 (Azure Networking)

Sep 2021 – Jun 2023 · 1 yr 9 mos · Redmond, Washington, United States

Anheuser-busch inbev

3 roles

Director, Product Owner

Promoted

Mar 2021 – Sep 2021 · 6 mos

Global Manager - Analytics

Promoted

Feb 2020 – Mar 2021 · 1 yr 1 mo

Leading several high-impact advanced analytics and research projects in collaboration with MIT professors.

Global Solutions Tech Intern - Analytics

Jun 2019 – Aug 2019 · 2 mos · San Francisco Bay Area

Collaborated with cross-functional teams of ML engineers and business heads, and devised the project plan for ML automation of annotation of video data. Analyzed ~40k hours of video data to derive features and accuracy metrics. Increased human labeling efficiency by ~45% and reduced workload by 31% using classification models for event detection and scene identification.

Georgia institute of technology

Graduate Teaching Assistant

Aug 2019 – Dec 2019 · 4 mos · Greater Atlanta Area

GTA for Machine Learning (CSE 6740)

Georgia institute of technology

Graduate Teaching Assistant

Jan 2019 – May 2019 · 4 mos · Georgia

Teaching Assistant for Data Analytics for Business

State street

Data Scientist

Aug 2017 – Jul 2018 · 11 mos · Bengaluru, Karnataka, India

Worked with cross-functional teams for building predictive and descriptive models in R and SAS using 20-25 years of financial data. Developed deposit rate prediction model in R using time series analysis, exponential fitting & autoregressive distributed lag (ARDL) modeling. Designed automated ongoing monitoring and recalibration process for models using statistical tests to determine parameter threshold values and outliers.

Goldman sachs

Quantitative Analyst (Strats)

Jun 2014 – Aug 2017 · 3 yrs 2 mos · Bengaluru, Karnataka, India

Collaborated with Portfolio Managers (PMs) and research teams to develop trading strategies and research tools for asset allocation and risk analysis. Redesigned end-to-end liability infrastructure with continuous feedback from PMs and reduced manual error by ~40% in uploading cashflows data. Increased trading efficiency by 10% by designing a risk dashboard for analytics

Bosch engineering and business solutions

Data Analyst Intern

May 2013 – Jul 2013 · 2 mos · Bengaluru, Karnataka, India

Proposed a real-time, non-intrusive driver drowsiness detection algorithm using spectral analysis of heart rate time series. Extracted various time-domain and frequency-domain parameters from the heart rate time series, and employed curve fitting methods to identify trends in the parameter values in MATLAB.