Data Analyst with over 4 years of experience in business intelligence, data management and analytics. Strong understanding and practical knowledge of technologies such as Java, SQL, Python, Hadoop, Tableau, HTML. Background in leading significant projects and managing technical teams in a fast paced environment.
Data Analyst with over 4 years of experience in business intelligence, data management and analytics. Strong understanding and practical knowledge of technologies such as Java, SQL, Python, Hadoop, Tableau, HTML. Background in leading significant projects and managing technical teams in a fast paced environment.
CV | Sham Sunder | Data | Database | Business Intelligence | .NetSham Sunder
Lead developer having 13+ years of job and 7 years of experience on my own financial accounting product, looking for an organization that provides opportunities for professional growth & increasing responsibility. Passionate to trace the path of success through continuous technical and domain learning and by making a significant contribution to the organization.
Presented the hands-on session on “Introduction to Big Data Analysis” at Dayananda Sagar University. Around 150+ University students benefitted from this session.
UTAD - Jornadas de Informática - Potential of Big DataMarco Silva
Short Presentation given at the Universidade de Tras dos Montes (UTAD) IT event for students and faculty members. The talk is meant to be an overview of Big Data and how microsoft technologies tackle that subject and how students could leverage these tools on their projects and future.
Apache Spark for Machine Learning with High Dimensional Labels: Spark Summit ...Spark Summit
This talk will cover the tools we used, the hurdles we faced and the work arounds we developed with the help from Databricks support in our attempt to build a custom machine learning model and use it to predict the TV ratings for different networks and demographics.
The Apache Spark machine learning and dataframe APIs make it incredibly easy to produce a machine learning pipeline to solve an archetypal supervised learning problem. In our applications at Cadent, we face a challenge with high dimensional labels and relatively low dimensional features; at first pass such a problem is all but intractable but thanks to a large number of historical records and the tools available in Apache Spark, we were able to construct a multi-stage model capable of forecasting with sufficient accuracy to drive the business application.
Over the course of our work we have come across many tools that made our lives easier, and others that forced work around. In this talk we will review our custom multi-stage methodology, review the challenges we faced and walk through the key steps that made our project successful.
Full-Time Roles : Business Intelligence Analyst, Data Analyst
Skills : Python, R, SQL, Machine Learning, Deep Learning
Tableau, Power Bi, Google Analytics,
Apache Spark
This talk will provide overview of big data software engineering and software engineering for big data as the tow fields need integrated. The interplay between the two field of research applications of Data Science and Software Engineering will enhance future perspective for a safe, secure, and sustainable approaches to data science and application of data science for 50 years of software engineering data that exists.
Manager in the filed of BPMA, providing services in below areas:
- Data Warehousing
- Business Intelligence
- SDLC (Waterfall & Agile)
- Business Analysis
- Project Management
- MIS & Reporting
- CRM development
- Artificial Intelligence
- Production Support
- Data Quality & Governance framework
- System Integration
Skill Set:
Sql, SAS, Qlik sense, SAP BO
CV | Sham Sunder | Data | Database | Business Intelligence | .NetSham Sunder
Lead developer having 13+ years of job and 7 years of experience on my own financial accounting product, looking for an organization that provides opportunities for professional growth & increasing responsibility. Passionate to trace the path of success through continuous technical and domain learning and by making a significant contribution to the organization.
Presented the hands-on session on “Introduction to Big Data Analysis” at Dayananda Sagar University. Around 150+ University students benefitted from this session.
UTAD - Jornadas de Informática - Potential of Big DataMarco Silva
Short Presentation given at the Universidade de Tras dos Montes (UTAD) IT event for students and faculty members. The talk is meant to be an overview of Big Data and how microsoft technologies tackle that subject and how students could leverage these tools on their projects and future.
Apache Spark for Machine Learning with High Dimensional Labels: Spark Summit ...Spark Summit
This talk will cover the tools we used, the hurdles we faced and the work arounds we developed with the help from Databricks support in our attempt to build a custom machine learning model and use it to predict the TV ratings for different networks and demographics.
The Apache Spark machine learning and dataframe APIs make it incredibly easy to produce a machine learning pipeline to solve an archetypal supervised learning problem. In our applications at Cadent, we face a challenge with high dimensional labels and relatively low dimensional features; at first pass such a problem is all but intractable but thanks to a large number of historical records and the tools available in Apache Spark, we were able to construct a multi-stage model capable of forecasting with sufficient accuracy to drive the business application.
Over the course of our work we have come across many tools that made our lives easier, and others that forced work around. In this talk we will review our custom multi-stage methodology, review the challenges we faced and walk through the key steps that made our project successful.
Full-Time Roles : Business Intelligence Analyst, Data Analyst
Skills : Python, R, SQL, Machine Learning, Deep Learning
Tableau, Power Bi, Google Analytics,
Apache Spark
This talk will provide overview of big data software engineering and software engineering for big data as the tow fields need integrated. The interplay between the two field of research applications of Data Science and Software Engineering will enhance future perspective for a safe, secure, and sustainable approaches to data science and application of data science for 50 years of software engineering data that exists.
Manager in the filed of BPMA, providing services in below areas:
- Data Warehousing
- Business Intelligence
- SDLC (Waterfall & Agile)
- Business Analysis
- Project Management
- MIS & Reporting
- CRM development
- Artificial Intelligence
- Production Support
- Data Quality & Governance framework
- System Integration
Skill Set:
Sql, SAS, Qlik sense, SAP BO
Similar to Rahul Chauhan - Data Scientist Resume.pdf (20)
Want to move your career forward? Looking to build your leadership skills while helping others learn, grow, and improve their skills? Seeking someone who can guide you in achieving these goals?
You can accomplish this through a mentoring partnership. Learn more about the PMISSC Mentoring Program, where you’ll discover the incredible benefits of becoming a mentor or mentee. This program is designed to foster professional growth, enhance skills, and build a strong network within the project management community. Whether you're looking to share your expertise or seeking guidance to advance your career, the PMI Mentoring Program offers valuable opportunities for personal and professional development.
Watch this to learn:
* Overview of the PMISSC Mentoring Program: Mission, vision, and objectives.
* Benefits for Volunteer Mentors: Professional development, networking, personal satisfaction, and recognition.
* Advantages for Mentees: Career advancement, skill development, networking, and confidence building.
* Program Structure and Expectations: Mentor-mentee matching process, program phases, and time commitment.
* Success Stories and Testimonials: Inspiring examples from past participants.
* How to Get Involved: Steps to participate and resources available for support throughout the program.
Learn how you can make a difference in the project management community and take the next step in your professional journey.
About Hector Del Castillo
Hector is VP of Professional Development at the PMI Silver Spring Chapter, and CEO of Bold PM. He's a mid-market growth product executive and changemaker. He works with mid-market product-driven software executives to solve their biggest growth problems. He scales product growth, optimizes ops and builds loyal customers. He has reduced customer churn 33%, and boosted sales 47% for clients. He makes a significant impact by building and launching world-changing AI-powered products. If you're looking for an engaging and inspiring speaker to spark creativity and innovation within your organization, set up an appointment to discuss your specific needs and identify a suitable topic to inspire your audience at your next corporate conference, symposium, executive summit, or planning retreat.
About PMI Silver Spring Chapter
We are a branch of the Project Management Institute. We offer a platform for project management professionals in Silver Spring, MD, and the DC/Baltimore metro area. Monthly meetings facilitate networking, knowledge sharing, and professional development. For event details, visit pmissc.org.
The Impact of Artificial Intelligence on Modern Society.pdfssuser3e63fc
Just a game Assignment 3
1. What has made Louis Vuitton's business model successful in the Japanese luxury market?
2. What are the opportunities and challenges for Louis Vuitton in Japan?
3. What are the specifics of the Japanese fashion luxury market?
4. How did Louis Vuitton enter into the Japanese market originally? What were the other entry strategies it adopted later to strengthen its presence?
5. Will Louis Vuitton have any new challenges arise due to the global financial crisis? How does it overcome the new challenges?Assignment 3
1. What has made Louis Vuitton's business model successful in the Japanese luxury market?
2. What are the opportunities and challenges for Louis Vuitton in Japan?
3. What are the specifics of the Japanese fashion luxury market?
4. How did Louis Vuitton enter into the Japanese market originally? What were the other entry strategies it adopted later to strengthen its presence?
5. Will Louis Vuitton have any new challenges arise due to the global financial crisis? How does it overcome the new challenges?Assignment 3
1. What has made Louis Vuitton's business model successful in the Japanese luxury market?
2. What are the opportunities and challenges for Louis Vuitton in Japan?
3. What are the specifics of the Japanese fashion luxury market?
4. How did Louis Vuitton enter into the Japanese market originally? What were the other entry strategies it adopted later to strengthen its presence?
5. Will Louis Vuitton have any new challenges arise due to the global financial crisis? How does it overcome the new challenges?
1. RAHUL CHAUHAN
720-755-4224 • rach3246@colorado.edu • LinkedIn • GitHub
EDUCATION
MS in Data Science 3.83/4.00
University of Colorado Boulder, CO, USA 08/22 – 05/24
B. Tech in Information Technology 8.39/10.00
University of Mumbai, MH, IND 08/17 – 05/21
SKILLS
Programming & Databases: Python, R, C#, SAS, SQL (MySQL, PostgreSQL, Cassandra DataStax)
Data Science & Machine Learning: Statistical Analysis, Machine Learning (SVM, Isolation Forests, Decision Trees), Neural
Networks (LSTM, GRU, CNN, ANN), NLP (NLTK, VADER, Word2Vec), Predictive Modeling, Time Series Analysis, Data
Manipulation (Pandas, NumPy), Big Data (Hadoop, Spark, Kafka), MLOps (CI/CD, model monitoring)
Visualization & Platforms: Power BI, Tableau, Excel, SAP, Kubernetes, Docker, OpenShift V2
RESEARCH EXPERIENCE
Graduate Research Assistant
Leeds School of Business, University of Colorado at Boulder, CO, USA 01/24 – 05/24
• Utilized NLP techniques (Word2Vec, VADER, LDA) to analyze 500+ comments on corporate gun violence stances, achieving
80.67% prediction accuracy
• Automated the collection and literature review from 1,500 market research papers using document parsing algorithms, reducing
manual effort by 90% and accelerating the research process by 35%
Data Scientist (Remote) [Medium Article]
99P labs, Honda Research Institute, CA, USA 01/24 – 05/24
• Architected a data pipeline for a telematics dataset of over 1M+ rows, developing driver profiling and behavior scoring systems
with Isolation Forest, XGBoost and ANN, yielding a prediction accuracy of 72.39%
• Designed a Power BI Dashboard for vehicle mobility management, visualizing fuel efficiency, cabin comfort, and speed
management to aid decision-making by 20%
WORK EXPERIENCE
Functional Consultant
LTIMindtree (Formerly known as Larsen & Toubro Infotech), MH, IN 07/21 – 07/22
• Leveraged SAP’s Plant Maintenance to conduct data-driven analysis, identifying trends and predicting maintenance needs, which
reduced equipment downtime and increased production efficiency by 12%
• Led the OneSAP system integration for Legacy Systems, using data analytics to streamline project management processes, assess
risks, and enhance decision-making, resulting in a successful transformation with a 40,000 euros turnover increase
PERSONAL PROJECTS
Insights on Delta Airlines using Machine Learning | RStudio | [Website Link]
• Extracted and analyzed over 20,000 Delta Airlines customer reviews from the Skytrax website. Employed data cleaning, EDA,
and various modeling techniques, improving prediction accuracy of customer sentiments by 11.52%
• Deployed machine learning models (Clustering, ARM, SVM, Regression, NB) to predict customer recommendations for Delta
Airlines, achieving the highest accuracy of 71.52% and identifying a 20% recommendation rate with an average rating of 3/5
Multivariate Time Series Analysis for Temperature Forecasting | Python | [Github Link]
• Engineered an LSTM-based neural network using TensorFlow, with an input layout of 7-time steps and 6 features. Achieved
training RMSE of 0.0279 and validation RMSE of 0.0296, reflecting high predictive accuracy
• Developed and implemented a deep learning model for temperature forecasting, including a 64-unit LSTM layer and two dense
layers for output processing, leading to the lowest RMSE scores observed in training and validation
Credit Card Transactions Grievance Dashboard | Tableau | [Tableau Link]
• Designed a Credit Card Fraud Complaints Dashboard using Tableau, enabling real-time tracking of 86,893 total grievances, and
significantly improving response times for effective and efficient fraud management strategies
• Created visual analytics with a “Weekly Trend” line graph and geographical data representation, enabling strategic decision-
making based on real-time grievance data and trends
OCD Patient Data Analytics and Visualization | SQL | [Github Link]
• Crafted a Health Analytics Dashboard using SQL and Excel, analyzing OCD diagnosis data for over 1,300 patients, thereby
enhancing strategic decisions based on detailed gender and ethnicity insights
• Streamlined monthly OCD diagnosis reporting through advanced SQL techniques, enabling efficient visualization in Power BI
and Excel, reducing manual data handling by 50%
Power BI-Driven Inventory Management Dashboard | Power BI | [Github Link]
• Established and implemented an Inventory Management Dashboard, optimizing data analysis and decision-making, achieving a
5.41 turnover ratio while managing a stock value of $77.3M across 303 SKUs
• Enhanced inventory management by visualizing data with bar graphs and pie charts, improving efficiency and accuracy