Jagan S Email & Phone Number
Who is Jagan S? Overview
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Jagan S is listed as Chief Engineer (ML and DS) at Samsung R&D Institute India, a with 6523 employees, based in Bengaluru, Karnataka, India. AeroLeads shows a matched LinkedIn profile for Jagan S.
Jagan S previously worked as Chief Engineer (ML/DS) at Samsung R&D Institute India and Senior Data Scientist at Ge Healthcare. Jagan S holds Master Of Science - Ms, Computer Science from Georgia Institute Of Technology.
Email format at Samsung R&D Institute India
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About Jagan S
Senior Data Scientist with ~6 years of experience in developing robust advanced analytics/Machine Learning solutions to develop insights which drive business action across multiple domains like Retail CRM, Supply chain and healthcare industry. Have played a key role in all stages of the data science project pipeline , stating from idea conceptualization, creating a viable business case , executing them using novel algorithms and creating production ready modules. Believes in a continuous learning approach and contributes to data science communities like Kaggle.Kaggle profile: https://www.kaggle.com/jagangupta/
Listed skills include R, Algorithms, Predictive Modeling, Data Analysis, and 17 others.
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Jagan S work experience
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Chief Engineer (Ml/Ds)
CurrentWorking on large scale Personalized Recommendation systems for Samsung's Ad targetting team.
Senior Data Scientist
Smart Troubleshooting for service incidents: Developed an NLP and Machine Learning based product for diagnosing issues of advanced medical devices (like CT,MRI) and recommending troubleshooting steps to service engineers, which led to productivity savings of around $50 million per year. The product involved the following major sub-projects: *Formulated and developed a novel (patented) semi-supervised data labelling process using an ensemble of diverse classifiers followed by feedback based (active learning) process to build reliable labelled training data *Developed two tier hierarchical prediction model (multi class classification) which pin points the machine issue *This involved incorporating large volume (>500 GB input datasets) data-sources(with very low SNR ratio) and processing semi and unstructured datasets (user written text data, machine log data, sensor based log data) *This process also involved modelling for high cardinality and high class imbalance using effective sampling and hierarchical classification with uncertainty thresholds *Created custom model explainability models (based on LIME) for machine codes to gain the trust of the users towards our predictions and hence boosting tool adoption and end user confidence in predictions *Model performance monitoring framework with embedded feedback mechanism in the tool for active evaluation of model in the field *Scaled up the tool from a single region to all regions while handling linguistic differences on text model performance *Co-designed Model Ops with data engineering team to facilitate easy model deployment and management in production in AWS platform *Recruited and mentored junior data scientists to create deliverables for the team *Created several POCs for ML evangelism across different orgs in GE (Some prominent examples include Graph based supply chain optimiser, Product Reliability feedback text clustering)
Data Scientist
Data Scientist at General Electric Healthcare.Working on problems with an NLP focus.
Decision Scientist
At Mu Sigma, I worked as a Decision scientist who works at the intersection of Math, Business, and Technology to solve complex business problems using Data. I have worked on a broad field of problems ranging from Extracting information from Text (NLP), Images(CNN, SSD) to predicting purchase patterns of customers ( Clustering, Regression) using a variety of tools like Python, R, Hadoop, Hive, Oozie.Key Projects: Customer Behavioural Segmentation: Enabled a major US retailer to make better marketing and merchandising decisions by segmenting their customer base of ~90M households based on their purchase pattern Omni-channel Propensity analysis: Increased Email CTR (Click Through Rate) from 1.6% to 3.1 % for a major US retailer among traditional Brick & Mortar shoppers by prioritising potential Omni-channel households through a look-alike model Customer Lifetime Value model: For a US retail major, created a CLTV framework to predict the total spend of a customer for the next 3 years. The framework was built across different tenure-based shopper groups to enable better marketing, using a suite of regression models along with migration probabilities. Fruit Defect detection: For I & D wing of a leading US retailer, built fruit defect detector and classifier using Deep Learning techniques(r-CNN, SSD) which predicts defects in Strawberries with an accuracy of 93.5%.
Jagan S education
Master Of Science - Ms, Computer Science
Bachelor Of Technology (B.Tech.), Mechanical Engineering, 8.3
High School, Computer Science, 1162/1200
Frequently asked questions about Jagan S
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What company does Jagan S work for?
Jagan S works for Samsung R&D Institute India.
What is Jagan S's role at Samsung R&D Institute India?
Jagan S is listed as Chief Engineer (ML and DS) at Samsung R&D Institute India.
Where is Jagan S based?
Jagan S is based in Bengaluru, Karnataka, India while working with Samsung R&D Institute India.
What companies has Jagan S worked for?
Jagan S has worked for Samsung R&D Institute India, Ge Healthcare, and Mu Sigma Inc..
How can I contact Jagan S?
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What schools did Jagan S attend?
Jagan S holds Master Of Science - Ms, Computer Science from Georgia Institute Of Technology.
What skills is Jagan S known for?
Jagan S is listed with skills including R, Algorithms, Predictive Modeling, Data Analysis, Tensorflow, Oozie, Data Analytics, and Hadoop.
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