Karthik Sriram Chandrashekar

Director of Engineering

San Francisco, California, United States14 yrs 3 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Led multi-million dollar data science initiatives at Netflix.
Innovated pricing strategies driving significant revenue growth.
Expert in building scalable data infrastructures and ML pipelines.

Stackforce AI infers this person is a Data Science and Engineering leader with expertise in scalable systems for the entertainment industry.

Contact

Skills

Core Skills

Data ScienceProduct StrategyStatistical ComputationMarket ResearchMachine LearningData EngineeringData AnalysisBig DataData InfrastructureDatabase DesignSoftware EngineeringQuality Assurance

Other Skills

EngineeringData Pipeline DesignProduct ExperimentationPersonalizationData PrivacyExperimentation SystemsStatistical AnalysisRevenue EstimationSparkHiveDistributed SystemsApache HadoopKafkaDatabase DevelopmentData Warehousing

About

I have over a decade of experience leading inter-disciplinary projects spanning software engineering, ML engineering, data engineering, causal inference & experimentation, and data-informed product strategy. I'm interested in leadership roles that require a blend of Data Science, Engineering and Product strategy.

Experience

14 yrs 3 mos

Total Experience

3 yrs 6 mos

Average Tenure

11 yrs 3 mos

Current Experience

Netflix

2 roles

Director, Data Science & Engineering

Promoted

Jan 2015 – Present · 11 yrs 3 mos

Led data science strategy for several multi-million-dollar initiatives. I work alongside Data Science, Engineering & Product leadership to shape Netflix's future as world's most successful entertainment business.
Some select high impact projects I've lead:
The Data Science Strategy for Netflix's Paid Sharing initiative which drove a multi-billion dollar revenue impact for Netflix
Pricing & Plans strategy & innovation - including introducing the Mobile plan in India through extensive go-to-market research, modeling and product experimentation.
ML Engineering for non-member experience personalization for optimizing signup/revenue.
Introducing a new experimentation identifier for all non-member experimentation at Netflix. This includes privacy, identifier lifecycle design, experimentation system and data pipeline/multi touch attribution design.
Data & Statistical Computation for estimating $ value of AB Test rollouts. The ability to say "We generated over $X Million in revenue vs x% lift in revenue metric" had broad impact across the entire 300+ member Growth org.

Data ScienceEngineeringProduct StrategyData Analysis

Software Engineer - Machine Learning

Jan 2015 – Present · 11 yrs 3 mos

Machine Learning Engineering for subscriber growth @ Netflix.
Data Engineering & Infrastructure for ML Pipelines
Applied ML for Reinforcement Learning, Classification, Clustering & Anomaly Detection
Spark, Pig, Hive, Presto
Software Engineering & Design for Product Innovation
Java, Scala, Python

Machine LearningData EngineeringSoftware EngineeringSparkHive

Groundtruth

Senior Software Engineer - Data Infrastructure

Jan 2014 – Jan 2015 · 1 yr · Mountain View, CA

Big Data@xAd
Building scalable data infrastructure for Science, Analytics and Reporting.
Interfacing with various Ad/Data partners for data exchange.
Architecting and operationalizing distributed systems and frameworks for massive scale data processing.
Apache Hadoop/YARN/Kafka/Storm/Samza/Zookeeper
Amazon EMR/S3/Redshift

Big DataData InfrastructureDistributed SystemsApache HadoopKafka

Epic

Software Developer - R&D (Databases)

Jan 2013 – Jan 2014 · 1 yr · Greater Madison Area

I was a Software Developer on the Cogito-DataWarehouse team. Cogito is Epic's newest Data Analytics product. The DataWarehouse team is focused on building a generic, flexible and extensible Data Warehouse product to address the extensive reporting and BI needs of Epic's customers who generate tremendous amounts of Healthcare data. Technologies: C#, ASP.NET, SQL Server 2012

Database DevelopmentData WarehousingSQL ServerDatabase DesignData Engineering

Media.net (directi group)

Machine Learning Engineer

Jan 2012 – Jan 2013 · 1 yr · Mumbai Metropolitan Region

Digital Contextual Advertising.
I was part of the keyword intelligence team that worked on delivering highly relevant online ads to publishers at a volume of billions of ads per month. Designed and built a real time analytics system for high volume data to improve targetted advertising and ad performance through real time machine learning which resulted in a significant upside in revenue across customers.
Contributed actively to the recruitment process of the organization. Designed, set and conducted several algorithmic interviews for off campus and on campus recruitment at India's most elite engineering institutions (BITS Pilani/IITs) in search of the best software development talent.
Knowledge/Technologies involved: Advanced Statistics, Machine Learning, High Scalability, Redis, Database Architecture, Data Analysis, Microsoft Excel, Java, PHP, SQL Server.

Machine LearningReal-time AnalyticsData Analysis

Juniper networks

Software Engineering

Jan 2012 – Jan 2012 · 0 mo · Bangalore

I was part of the Automation team of the client access wing of the Pulse Business Unit - Quality Assurance Department.
Was responsible for bettering the Testing Framework and scripting complex test cases in Perl for the Pulse 3.0 software of Juniper Networks.

AutomationTesting FrameworksPerlSoftware EngineeringQuality Assurance

The institute of mathematical sciences, chennai

Research, Theoretical Computer Science

Jan 2011 – Jan 2011 · 0 mo · Greater Chennai Area

I was selected to attend the summer school in Theoretical Computer Science. Various upcoming topics in Computer Science were discussed.

National center for antarctic and ocean research, goa

Research, Polar Remote Sensing Lab

Jan 2010 – Jan 2010 · 0 mo · Goa

I worked as a research assistant in the Polar Remote Sensing Lab, NCAOR, Goa. I designed statistical models for predictive analytics on Arctic sea ice cover using NASA's open geo data.