As a results driven individual, I have successfully translated business requirements into models that were continuously improved and delivered tangible results. My core competencies lie in leading machine learning projects end-to-end with the ultimate goal of improving customer experience and driving business impact.
Skills
5+ years of experience in machine learning, deep learning, data science, building ML Pipelines and data engineering
Machine Learning Engineer, 03/2018 - Current Viasat Inc. – WI, State,
Led the machine learning anti-spam efforts for iCloud mail and calendar. This included tClairening and evaluating spam models, scheduling tClairening pipelines, contributing to new feature enhancements in the models, and working with Privacy/Legal teams to ensure that all features and models were compliant with Apple’s broader stance on user’s data privacy and security
Deployed the first ever ML based anti-spam model for iCloud mail and calendar to production
Implemented the ability to run A/B experimentation in the calendar and mail systems. These A/B tests are now used to validate model performance prior to production
Automate the process of producing datasets for labeling and contributed to integration with labeling tools at Apple. Consolidated an effective approach for the evaluation of spam models in the absence of ground truth
Worked cross-functionally with various teams within ACS to develop reports and experimentation dashboards that can track the performance of production ML models
Maintenance and continuous improvement of production models post deployment
Responsible for driving efficiency to the core messaging engine for iCloud customers around their storage utilization by bringing machine learning and end-to-end optimization to the iCloud subscriptions funnel
Accountable for increasing storage tier conversion rates and improving the overall customer experience by reducing notifications and emails
Continuously driving the culture of data-driven decision making & optimization across the broader org through tech talks and representing the Apple Cloud ML team in various ML events across Apple
Instrumental in defining the trajectory of the only machine learning team within Apple Cloud Services (ACS) as one of the first few members. This includes defining the roadmap and the tech stack for the team
Hiring and mentoring team members
ICloud Big Data Analyst, 09/2016 - 02/2018 Angi Homeservices Inc. – New York City, NY,
Designed and built an alerting model to detect anomalous data in the incoming data streams. The model consists of a forecasting component which utilizes regression with regularization to generate predicted values of key performance indicators. The model has high sensitivity and specificity and requires minimal human intervention leading to a more robust tracking system
Used a graph-based analysis to uncover large extensive networks of fraudulent iCloud users. This was used to expose vulnerabilities in the account creation process that was abused in the form of credit card fraud
Determined existing fraud trends in the creation of iCloud accounts and worked cross functionally with the Fraud team in adding new rules to suppress future creation of similar accounts
Improved iCloud customer experience by studying the effects of product changes, iOS launches and new features with special focus on churn analysis
Implemented a classification model to uncover the contributing factors towards iCloud churn
Involved in efforts to increase iCloud revenue by increasing iCloud user engagement and defining metrics to measure the same
Built forecasting models to predict adoption rates of iOS/macOS and device sales
Data Analyst, 12/2014 - 08/2016 Apple, Inc. (Through Infosys, Ltd) – City, STATE,
Led efforts in the quarterly budget reviews to report on stats across the iCloud org
Performed investigatory analyses to uncover reasons behind churn across various iCloud apps and services
Designed, implemented and automated a predictive model, which uses ARIMA components to forecast critical key performance indicators
Built an interactive D3 dashboard to reflect the results of the forecasting model
Performed ad hoc analyses to estimate the performance and behavior of product releases using SQL and Python
Automated data extrapolation and interpolation processes utilizing crontab script automation and python scientific libraries such as pandas, numpy, scipy and statsmodels
Education and Training
Master of Science: Applied And Computational Mathematics, Expected in 08/2014 - Rochester Institute of Technology - Rochester, NY GPA:
Bachelor of Science: Information Science And Engineering, Expected in 06/2012 - Visveswariah Technological University, NMIT - Bangalore, India, GPA:
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