Gowtham Sai Panyam

Data Scientist

Bengaluru, Karnataka, India8 yrs 6 mos experience

Most Likely To SwitchAI Enabled

Key Highlights

Expert in Machine Learning and Deep Learning techniques.
Proficient in TensorFlow for advanced data modeling.
Strong background in data analysis and processing.

Stackforce AI infers this person is a Data Scientist with expertise in E-commerce and Machine Learning applications.

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Skills

Core Skills

Machine LearningDeep LearningData AnalysisData Processing

Other Skills

ARIMAAlgorithmsArtificial IntelligenceBuilding ModelsCCBOWComputer ScienceComputer VisionCosine SimilaritiesData VisualizationDensity Based ClusteringElasticSearchHTMLK-meansLSTM

About

Experienced Data Scientist with a demonstrated history of working in the internet industry. Skilled in Tensorflow, Deep learning, Python and Go. Strong information technology professional with a Bachelor of Technology focused in Computer Science from Indian Institute of Technology, Kanpur.

Experience

8 yrs 6 mos

Total Experience

2 yrs 10 mos

Average Tenure

4 yrs 10 mos

Current Experience

Flipkart

Data Scientist

Aug 2021 – Present · 4 yrs 10 mos · Bengaluru, Karnataka, India

TensorFlowDeep LearningPythonMachine Learning

Airtel x labs

Associate Data Scientist

Oct 2018 – Aug 2021 · 2 yrs 10 mos · Bengaluru, Karnataka, India

Sellerapp

Data Scientist

Nov 2017 – Sep 2018 · 10 mos · Bengaluru Area, India

Finding the amazon keywords for a particular product and ranking them with respect to the product relevancy. To address the above problem I have used SGNS(Skip Gram Negative Sampling) and CBOW(Continuous Bag Of Words) technique (introduced by Mikolov et al).
Implicitly factorized a word-context matrix, whose cells are the pointwise mutual information of the respective word and context pairs, shifted by a global constant. Using these word-content matrix, calculated Cosine Similarities.
Estimate the sales velocity of a Product given the Best Seller Rank on Amazon, used ARIMA and
LSTM models.

SGNSCBOWCosine SimilaritiesARIMALSTMMachine Learning+1

Aig

Internship

May 2016 – Jul 2016 · 2 mos · Bengaluru, Karnataka, India

Built a platform in which user uploads PDF, which is converted into standard JSON. The standard JSON ﬁles serves as input for the models like text classification, topic modelling Analysed the overall structure of a json data, and pre-processed the text using NLTK, RE python libraries. Extracted interesting terms from a data set by using term frequencies, stop-word removal and n-grams. Used Tensorflow library for classiﬁcation that predicts the high probable words responsible for classiﬁcation using CNN architecture. Studied the K-means algorithm and different Density based Clustering algorithms in detail and implemented them in various situations and hence got acquainted with their use cases and limitations.

Text ClassificationTopic ModellingNLTKTensorFlowK-meansDensity Based Clustering+2