Sleeba Paul
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Product Manager @ DocketAI: Agent fleet for Sales and Marketing | fmr TPM @ Ericsson Language Intelligence | TEDx Speaker | Learner | Maker |
Product Manager for AI/ML at DocketAI, where I own ML product lines. I also ship code on LiveAssist, which started as a weekend project and became a product SKU. Before DocketAI, I spent four years at Ericsson. Selected for the Early Career Program — Ericsson's global leadership pipeline with three rotations and an international assignment — which took me from ML engineering in Chennai to D-15 Labs in Santa Clara to strategic product management in Stockholm, and finally technical product management for Language Intelligence. Two IP disclosures in Radio Access Networks came out of that stretch. I've published at COMSNETS '22 and '23, spoken at TEDx and PyData, and created AuriaKathi — an AI Poet Artist sponsored by Microsoft, exhibited at the Florence Biennale and NeurIPS 2019. M.Tech in Power Systems. B.Tech in EEE. sleebapaul.github.io
University of Calicut
Master of Technology - MTech, Power Systems
January 1, 2014 – January 1, 2016
Cochin University of Science and Technology
Bachelor of Technology - BTech, Electrical and Electronics Engineering
January 1, 2009 – January 1, 2013
DocketAI
Product Manager
January 1, 2025 – Present
On-site
DocketAI
Senior Machine Learning Engineer
October 1, 2024 – January 1, 2025
On-site
Ericsson
Technical Product Manager
April 1, 2024 – October 1, 2024
Ericsson
Strategic Product Manager
June 1, 2023 – March 1, 2024
Ericsson
Machine Learning Engineer III and Ericsson Early Career Program Innovate Candidate
April 1, 2022 – May 1, 2023
Ericsson
Machine Learning Engineer II and Ericsson Early Career Program Innovate Candidate
August 1, 2021 – May 1, 2022
Ericsson
Machine Learning Engineer II
November 1, 2020 – August 1, 2021
Perleybrook Labs LLC
Machine Learning Engineer
July 1, 2017 – November 1, 2020
Bangalore, India
Unisave Marketing Networks (P) LTD
Junior Data Scientist
March 1, 2017 – June 1, 2017
Cochin Area, India
Unisave Marketing Networks (P) LTD
Data Scientist - Intern
November 1, 2016 – March 1, 2017
Cochin Area, India
LEELA ELECTRICPOWER SERVICES PRIVATE LIMITED
Intern
May 1, 2015 – June 1, 2015
Ernakulam
Calicut University
Graduate Teaching Assistant
August 1, 2014 – August 1, 2016
Thrissur
Beyond App | Bring back the historical figures to life
June 1, 2022 – March 1, 2023
* Conceived the idea and led a four-member team for "Beyond" project * Project philosophy: Creating an app to communicate with historical figures like Steve Jobs, Mahatma Gandhi, and Nelson Mandela to seek their perspectives even after their demise. * Brought back Mahatma Gandhi to life using generative AI technology. * With Beyond android app, achieved 100+ downloads in Android Play Store * Developed a Telegram bot version of the app and garnered ~1000+ users and featured in the Telegram bot archive * Introduced "The Persona Palette" feature: Allows users to create custom chat profiles, such as historical figures or personal interests, for an engaging and imaginative experience.
Auria Kathi - The first AI Poet Artist
October 1, 2018 – December 1, 2018
Auria generates a short poem, draws an abstract art based on the poem, and then color the picture depending upon a random mood. All these creative tasks are done without any human intervention. Auria featured in CreativeApplications.Net, Towards DataScience, Coding Blues, and Creative AI Newsletter. 1. https://www.creativeapplications.net/member-submissions/auria-kathi-an-ai-artist-living-in-the-cloud/ 2. https://towardsdatascience.com/auriakathi-596dfb8710d6 3. https://codingblues.com/2019/01/11/fabin-sleeba-and-wonderful-auria/ 4. https://us15.campaign-archive.com/?u=c7e080421931e2a646364e3ef&id=d1a15e8502 Read more about her at https://medium.com/@nurecas/auriakathi-596dfb8710d6
Gospel of LSTMs
June 1, 2018 – September 1, 2018
- Using LSTMs, a language model is built for Gospels of the Bible. - A machine authored Gospel is generated using the trained model. - Implemented in PyTorch. - Featured in Good Audience blog
Implementation of Content Extraction Via Tag Ratios(CETR) in Python
May 1, 2017 – June 1, 2017
Extracting content from web pages is a challenge since most of the modern web pages have a variety of content apart from the text. A straightforward approach may not exist.But research in this field has made tremendous progress with the help of machine learning. One such method is CETR(http://www3.nd.edu/~tweninge/cetr/) that extracts text based on tag ratios. It's based on the intuition that tag ratios are higher wherever there is text content.
PyThesaurus - A pip package to fetch synonyms and meanings from online dictionary sites
May 1, 2017 – November 1, 2017
This package gets you the synonyms and definitions of an inputted word from the best dictionary sites available online. Thesaurus.com Dictionary.com Though python provides lexical resources like WordNet, the variety of options it can provide will be poor when compares to the dictionary.com or the thesaurus.com. This will help the user to enhance their approaches when he/she is dealing with text mining, NLP techniques and much more.
Sentiment Analysis of Malayalam movie Take Off - 2017 based on bookmyshow.com reviews
March 1, 2017 – April 1, 2017
Malayalam film industry was beholding the growing buzz about the movie "Take Off". I couldn't watch the movie but when I went through the reviews at bookmyshow.com, I thought I could do a sentiment analysis on them and get the overall 'feeling' people had experienced at the theatre. Thanks to Python, I could easily scrape the data I required from the following URL. https://in.bookmyshow.com/movies/take-off/ET00052469 Using some beneficial packages in R, I managed to perform Sentiment Analysis and extracted this resulting bar diagram. The returns show that "Take-Off" is indeed a great movie and people loved it. Happy Nurse's Day in advance!
Handwriting Recognition (Letters) Using Artificial Neural Networks (ANN)
May 1, 2016 – June 1, 2016
Training NN using gray-scale intensity of image of hand-written letter and getting the parameters for prediction was the first step. The prediction of new examples are based on the parameters calculated from the training set. The programming environment is MATLAB.
Islanding and Power Quality issues Detection and Classification using Wavelet Transform and ANN
November 1, 2015 – October 1, 2016
Unlike Fourier transforms, the Wavelet Transform (WT) can be used in non-periodic, discontinuous and transient signal decomposition. The analysis is based on the negative sequence voltage (Measure of unbalance) which is extracted at the time of Islanding and PQ Issues.The WT indices are calculated and used to train a Multi Class ANN. Using Microsoft Azure ML Studio, the training is done and deployed it as a Web Service. Using a GUI built on Python, the API is accessed whenever needed, to get the prediction results.
Automated DC motor starter
December 1, 2011 – April 1, 2012
The normal DC motor mechanical starter (3 point nd 4 point) is automated by means of power electronics. Series connected thyristors are triggered using a micro controller in regular intervals of time and motor reaches the rated speed in a defined time. The initial high current flow risk is avoided. No mechanical parts are used and thereby sparks and other mechanical losses can be avoided. No manual control is needed as switching is controlled by a micro controller..
AI Product Management Specialization
Coursera
June 24, 2026 – Present
Machine Learning Modeling Pipelines in Production
Coursera
June 24, 2026 – Present
Machine Learning Data Lifecycle in Production
Coursera
June 24, 2026 – Present
Applied Plotting, Charting & Data Representation in Python
Coursera
June 24, 2026 – Present
How to Win a Data Science Competition: Learn from Top Kagglers (with Honors)
Coursera
June 24, 2026 – Present
Introduction to Deep Learning (with Honors)
Coursera
June 24, 2026 – Present
Sequence Models
Coursera
June 24, 2026 – Present
Introduction to Shell for Data Science
DataCamp
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Human Factors in AI
Coursera
June 24, 2026 – Present
Machine Learning Foundations for Product Managers
Coursera
June 24, 2026 – Present
Introduction to Machine Learning in Production
Coursera
June 24, 2026 – Present
Bayesian Methods for Machine Learning
Coursera
June 24, 2026 – Present
Data Structures
Coursera
June 24, 2026 – Present
Algorithmic Toolbox
Coursera
June 24, 2026 – Present
Big Data Foundations - Level 1
IBM
June 24, 2026 – Present
Introduction to Computer Science and Programming Using Python - MIT
edX
June 24, 2026 – Present
Early Career Program (2021 - 2023)
Ericsson
June 24, 2026 – Present
Solar Energy - TU Delft
edX
June 24, 2026 – Present
Data Science Essentials - Microsoft
edX
June 24, 2026 – Present
Computational Probability and Inference
edX
June 24, 2026 – Present
Deep Learning with TensorFlow
IBM
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Deep Learning Specialization
Coursera
June 24, 2026 – Present
Managing Machine Learning Projects
Coursera
June 24, 2026 – Present
Machine Learning
Coursera Course Certificates
June 24, 2026 – Present
Introduction to R
DataCamp
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Introduction to Git for Data Science
DataCamp
June 24, 2026 – Present
Deploying Machine Learning Models in Production
Coursera
June 24, 2026 – Present
Machine Learning Engineering for Production (MLOps) Specialization (4 Courses)
Coursera
June 24, 2026 – Present
Ericsson Early Career Program Established Market Module
Northeastern University
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse personal projects, ranging from generative AI applications ('Beyond App', 'Auria Kathi') to sentiment analysis and content extraction, demonstrate a strong passion for data science and AI beyond their professional roles. Their progression from Machine Learning Engineer to Product Manager at Ericsson and DocketAI shows adaptability and a willingness to take on different challenges. While the target role is 'Data Analyst', their background leans heavily towards Machine Learning Engineering and Product Management, which might indicate a potential mismatch in day-to-day responsibilities if the Data Analyst role is purely focused on reporting and basic analytics. However, if the Data Analyst role involves advanced analytics, predictive modeling, and contributing to data product strategy, their profile aligns well. The breadth of their certifications also shows a commitment to continuous learning.
Soft Skills & Operational Fit
The candidate's experience as a Product Manager and their involvement in coordinating AI projects at Ericsson D-15 labs suggest strong leadership, stakeholder management, and cross-functional team collaboration skills. Their personal projects, such as 'Beyond App' and 'Auria Kathi', demonstrate initiative, creativity, and the ability to drive projects from conception to deployment. These attributes indicate a good operational fit for roles requiring independent problem-solving and collaborative work.