Data Scientist Summer Intern | SAS Certified | Machine Learning and AI Enthusiast | Data Storyteller
Welcome to my page, thank you for taking the time to stop by!
I am Nitesh, an analytics and data science professional!
MS in Business Analytics Oklahoma State University, Stillwater - Class of 2020. I am constantly developing skills that will help me turn data into information, and information into insight. Before I started grad school, I worked as a Software Engineer for nearly 6 years, where I developed supply chain data management software products at Zyme/E2open.
Scroll down, to find out more!
· Supply chain analytics consulting for a large membership-only retail warehouse club owned and operated by the largest retailer in the world
· Evaluated software, built a PowerBI application to visualize COGS for Insurance underwriting and inspections business.
· Analyzed cash deficit and found 40% weekly and 44% cases monthly, that helped renegotiate contract with a client.
· Built predictive models using Scikit-learn to explain and predict costs, descriptive analytics to visualize production.
· Worked on an ongoing project to evaluate effectiveness of a program for teenagers using data science.
· Reduced search and validation times in API’s by using Lucene indexes from several minutes to a few nanoseconds
· Saved 180 man-hours/month, using fewer resources & real- time data sync by replacing ETL workflows on proprietary platforms with Java components, improved memory utilization by tweaking garbage collector settings
· Continuously improved products by periodic technology updates, improved Performance, Scalability, Reliability of the product, security to adhere to ESAPI standards and automated reports using MySQL stored procedures and triggers
· Lead a team three engineers and release cycles, mentored three interns and involved in interviewing new candidates
· Prepared POC’s of new software libraries and explored tools and process changes and undertook Kaizen initiatives
· Recommended an alternate design of the A-Pump assembly line that required 30% fewer operators
GPA: 3.83
GPA: 3.5
I love reading books and learning new things about the world everyday - it is something that helps me stay excited! Although a majority of the books I have read are fiction and fantasy, I am not constrained to any particular genres - please HMU with your favourties, and I will add them to my list!
I try to implement the data science conceepts I learn, so that I can understand them better. Here are a few of my machine learning projects :
1. Analyzing Factors Impacting Suicidal Behavior in American Youth –by Latent Class Analysis, Survey Logistic Regression
2. Redesigned marketing strategy for an e-signature company using marketing mix modeling, basic time-series analysis
3. Loan recovery strategy comparison and analysis using predictive modeling and unsupervised learning for GM Financial
4. Elixir otherworldly coffee: applying location analytics concepts using ArcGIS to determine best store location
5. Case Study: Detecting “Kicked” cars for Carvana using Exploratory Data Analysis and Decision Trees
6. Case Study: Redesigning sales strategy for a cosmetics company by analysis of various customer groups using ANOVA
7. Case Study: Customer Churn prediction for a subscription-based business using logistic regression
I enjoy the adrenaline rush that comes with competing, and working with a team where we can brainstorm ideas! I am thankful to these opportunites - I believe the experience has given me valuable skills that no lectures can teach! Here are a few of my proudest moments - competition prizes, certificates and volunteering!