Data Scientist Sales Representative
Resume:
Shradhit Subudhi
shradhit.com linkedin.com/in/shradhit/ github.com/shradhit
New Jersey 07029
adxsi1@r.postjobfree.com
Professional Experience
ZS Associates, Inc. New York City Data Scientist Feb 2020 - Present Design, develop and execute high-impact analytics solutions. Experience with high volume, structured & unstructured data sets to help clients make better fact-based decisions. Some of the projects are listed below:
Omnichannel Dynamic Targeting: Led a team of 2 Data Scientists and 2 Data Engineers to support a big pharma client by developing dynamic targeting algorithms leveraging AI and optimization techniques. The project aimed to deliver a weekly call plan for Neuroscience and Infectious Diseases sales representatives comprising target customers and prescribing messages to engage customers effectively. The overall initiative of dynamic targeting improved sales by 35% . Computational Phenotyping: Led implementation of an AI tool to generate a generalizable vector representation of a patient’s medical state. Utilized NLP and DL techniques to obtain the medical code level vector embedding, and converted the medical code vectors to patient level by probability-based weight averaging techniques. Post which, a patient similarity network was constructed to maximize homogeneity within and heterogeneity among groups. The model accurately identified spatial and temporal patterns that distinguished diseases (in our case: NSCLC, AD, CKD, MS). The model helped us achieve a rand index of 70%. White Paper:: https://shorturl.at/cdht0 Synthetic Control Arm: Led the implementation of techniques to conduct clinical trials with a synthetic control arm. Identified similar patients in real-world data using inclusion/exclusion criteria.Utilized propensity score matching methods to minimize bias when comparing treatment and control datasets—calculated treatment effects for randomized control trials.
Covid Visitation Monitor: Developed a tool to monitor the visitation policy across all hospitals and group practices in the US. This data helped amend the call plan for the sales representative team based on access rules & regulations for the big pharma sales representatives.
Veritonic, Inc. New York City Data Scientist, Intern June 2019 - Dec 2019 Built deep neural network based AI modules to detect gender, emotions, and instruments in audio data. This allowed for a deeper understanding of the resonance of radio and podcast advertisements with target audiences. Automated tags were used as input to a broader dataset to rate audio and increase ROI for products and client firms. Key Aspects of the project include audio analysis, MFCC extraction, spectrogram generation, the model selection that enhances the selected metric, deep learning, model deployment, and Tools used include Librosa, Keras, TensorFlow, Sklearn, etc. Education
Rutgers University, Rutgers Business School, NJ Sep 2018 - Dec 2019 State University Of New Jersey
Masters in Information Technology and Analytics GPA: 3.717 Graduate Teaching Assistant of Data Analytics, Decision Making, Analytics of Business Intelligence, and Business Forecasting for Prof Sergei Schreider Relevant Coursework: Probability, Data Mining, Data Analytics, Decision Making, Forecasting, Financial Time Series, Databases, Business Intelligence, Software Development
College of Engineering Pune, India May 2014 - June 2018 Autonomous College of Government of Maharashtra
Bachelor of Technology in Computer Engineering SGPA: 8.62 (final semester) Relevant Coursework: Machine Learning, Advanced Database, Calculus, Optimization Technical Summary
Languages : Python, R, SQL, C/C++, git,
HTML/CSS, PySpark
Libraries/Frameworks : Scikit-Learn, Pandas,
Numpy, TensorFlow, PyTorch, Plotly, GraphX
Tools: Excel, Word, PowerPoint, Access, G
Suite, Jekyll, Power BI, Tableau, Neo4j
Knowledge Area: Supervised, Unsupervised,
regression, pattern, trend identification,
TensorFlow, Anomaly detection, time series,
outlier detection, data mining, visualization,
deep learning, computer vision, business
intelligence, redshift, recommendation
engines, Reinforcement learning, data
warehousing, MongoDB, document
clustering, text classification, Spark RedShift
Certifications
Introduction to Data Science in Python by
University of Michigan
Applied Plotting, Charting & Data
Representation in Python by University of
Michigan
Applied Machine Learning in Python by
University of Michigan
Applied Text Mining by University of
Michigan
Leadership Roles
Founder & Co-Secretary, Software
Development Section, CoEP
Team Lead, Smart India Hackathon
Class Representative, B.Tech Computer
Engineering from 2014-2018
Web Team Head for ED Cell, COEP
Mathematics Teacher (Volunteer) at St.
Jude India
Achievements
7th Rank in Public ML challenge, predicting
if a person has COVID looking at Lung CT Scan
Images
4th in B.Tech Project Competition for
Anecdote Detection System held at College of
Engineering Pune
Among Top 1 percentile in Grade 12th HSC -
Maharashtra, India State Board
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