Apr 2022 – Apr 2024 · 2 yrs · Bengaluru, Karnataka, India

• As a seasoned project manager in the dynamic field of data science, I excel in driving successful project outcomes through meticulous planning, effective team collaboration, and a commitment to ethical considerations. My experience encompasses the strategic oversight of multidisciplinary teams, implementing agile methodologies, and focusing on continuous improvement through monitoring, evaluation, and risk management. With a proven ability to navigate the complexities of data science projects, I am poised to contribute to the success of organizations seeking a results-oriented and adaptable project management leader in the data science arena.
• Key Driven: Project Planning and Execution, Team Collaboration and Leadership, Communication Excellence, Risk Management, Monitoring and Evaluation, Agile Methodologies, and Ethical Considerations in Data Science.
• 1. Sales Campaigns Prioritized Account List Prediction
• 2. Ideal Customer Profiler using Machine Learning
• 3. Product recommendation using Machine Learning
• 4. Hunting POD list generation using Machine Learning
• 5. Net New account finding and Target customers using Machine Learning
• Key Result Areas:
• Leading a team of 15 in strategic planning, team management, software development, and project oversight.
• Leveraging FinBi for extracting historical booking data, performing ETL processes, and segregating data into train and test datasets.
• Developing a propensity-to-buy model to identify high-potential accounts for IoT product sales.
• Spearheading data extraction, preprocessing, and ETL tasks for Cisco Sales data.
• Designing and implementing an integrated sales data model based on various metrics.
• Creating and refining clustering algorithms to target accounts with high IoT buying intent.
• Implement recommendation models and evaluate their efficacy for better results.
• Employing machine learning algorithms to identify target accounts and convert results into actionable datasets.

May 2021 – Apr 2022 · 11 mos · Bengaluru, Karnataka, India

• Co2 Emission Real-Time Data Analysis
• The Machine Learning model builds upon the Co2 data. The project's primary goal is to identify increasing emissions in the different understanding of the pattern of pollution in the world. Data was collected from multiple sources then created the data pipeline for the entire data then built Machine Learning techniques to understand the data behavior and then created the dashboard.
• Roles and responsibility
• Architecture design and implementation of Machine Learning-based Security Platform for the Thought Works. IoT network provides insight into CO2 emission based on implemented prediction, pattern analysis, and forecasting.
• Created a Machine Learning algorithm to identify the segmentation, and emission pattern behavior, analyze the carbon emission caused at the region level, and pattern identification using a clustering algorithm.
• Implemented a complex ML-based GCP cloud solution to detect Co2 in real-time.
• Market Optimization:
• Generated Insights that helped the customer to understand the market behavior and its effect on the jobs considering the weather factors.
• Created Log Based Linear Model at the Monthly level for different states in the USA, which can predict the likelihood of the jobs. Came up with a model that gives the client a simulation of how to divide the marketing spend weekly.
• Designed a slope-based optimization approach that gives the client an efficient way to divide the overall marketing budget across the four marketing categories and helps to achieve improved ROAS. Predicted the cancellation rate for the number of leads converted into business. And created capacity planning as an option for each state, which helps the business adjust its capacity.
• It has created a model for the saturation point approach that will help the business know the maximum budget that can be spent across a particular month and the maximized number of jobs across each marketing channel.

Aug 2016 – Apr 2021 · 4 yrs 8 mos · Bangalore

• Data Sciences, Cisco Web-Ex
• Analyzing big data for various customers and providing data insights.
• Developing statistical and predictive models to optimize the cost and turnaround time.
• Providing a solution approach to maximize the Monthly/Annual recurring revenue.
• Developing a cost-effective analytical solution by minimizing the cost and reducing the usage of commercial analytical tools for Big Data, HUE environment, Tableau.
• Implementing the NLP technique to understand customer behaviour.
• Major Projects Undertaken:
• AT&T ML Security Incidents and Risk Prediction
• Tools and Environment: Google Cloud Platform, Hadoop, Excel, Python, Node.JS, Jupyter Notebook,
• Visual Studio Code, JavaScript, HTML, CSS
• Cisco's Project Matrix
• Tools and Environment: Python, Plotly, various machine learning algorithms, and Django
• Cisco's Multi-description Text Classification
• Tools and Environment: Python, Scikit-Learn, Pandas, Matplotlib, Numpy, Flask, Logistic Regression, (Multinomial) Naive Bayes, Linear Support Vector Machine.
• Cisco's Topic Modelling using Python
• Tools and Environment: Python, Spacy, NLTK, Gensim, pyLDAvis, and LDA, Cisco Cloud
• Cisco's Customer Churn and Time Series Analysis and Forecasting
• Tools and Environment: Cisco Cloud, Excel, Python, Logistic Regression, Tableau, and Machine Learning techniques
• Cisco's Automated Voice Assistance (IVR)
• Tools and Environment: Dialog-flow, Big Query, Firebase, Google Calendar, GCP, and Cisco Cloud
• Cisco's Description Classification is based on aspects
• Tools and Environment: Python, NLTK, Gensim, Scikit-Learn, Tensorflow, Keras, and Cisco Cloud
• Cisco's Customer Experience Score
• Tools and Environment: Excel, Tableau, and Python, and Cisco Cloud
• AT&T's KPI Correlation
• Tools and Environment: Python, Plotly, Seaborn, ML Technique, and Cisco Cloud

Mar 2015 – Aug 2016 · 1 yr 5 mos · Bengaluru Area, India

• Analyse Data using R, Hadoop , Apache Hive, Apache Pig, ZoomData, Splunk, Etc... Implementation project POC, and giving suggestion for particular tools for project requirement.