Amit Kulkarni

MANAGEMENT CONSULTANT | KAGGLE EXPERT

18 YRS EXPERIENCE . BENGALURU . amitvkulkarni2@gmail.com

Data Science | Business Advisory | Consulting | Blogging


A certified data science practitioner with 17 years of experience. Currently, leading the digital and business advisory teams at Arcadis Consulting. In the past, I have served as a Consultant for CTO's office at Cognizant Technology Solutions and have worked as a Sr Consultant delivering data science solutions for CPG clients at Mindtree. I have authored series of articles on the latest trends in data science on analytics platforms like Analytics Vidhya and Medium.

My recent blogs on MLOps and Data Version Control (DVC) are featured in the August edition of Heartbeat 2021. I am passionate about contributing to the open-source community with analytics applications/solutions built with various open-source frameworks namely R Shiny, Plotly dash, DVC, and MLOps.

I write for several publications like AI Advances, Illumination, Data Driven Investor, Python in Plain English, Illumination Mirror, Classy Endeavors, GoPen AI, Lampshade of Illumination and Analytics Vidhya.

Experience



 
 
 
 
 

TECHNICAL DISCIPLINE LEAD

ARCADIS CONSULTING

March 2019 – Present | Bengaluru, India
I lead digital projects for Water Business Line and Business Advisory teams. I am leading a 20-member team which works on various projects ranging from Power BI / Tableau dashboards, web development, automation with UiPath, machine learning using R, Python and Azure. The role involves working with high performing teams and leading innovation in product development.
 
 
 
 
 

SENIOR CONSULTANT – ANALYTICS

Mindtree

April 2017 – March 2019 | Bengaluru, India
I was leading an 8-member team and was involved in designing and execution of pilot experiments & analysis, building predictive models, measure & report model performance for a major Retail CPG customer. I coordinated with the team of 3 data scientists working on 5 different projects. I lead the team which implemented analytics solution for ice cream market in Ecuador for the first time which helped sales growth of 5% QoQ.
 
 
 
 
 

SENIOR BUSINESS ANALYST

Cognizant Technology Solutions

March 2007 – April 2017 | Bengaluru, India
The role involved assisting all the business units of cognizant on adaptation of new technologies in collaboration with business unit heads, technology COE’s and marketing teams. Being part of CTO’s office, the role also involved communicating the strategies to be adopted across organization and publishing the vision of cognizant leadership through blogs, newsletters, tech talks, yammer and social media. Prior to this role, I worked as Associate where I was leading a 10 member COE team specialized on Adobe technologies and as Senior Associate, I worked on technology consulting and proposals for Insurance vertical.

Education



Visvesvaraya Technological University

BE - Mechanical Engineering | Sep 2002 - Jul 2006

Symbiosis University (SCDL)

PGDCRM | Apr 2012 - Feb 2014

Microsoft Certified: Azure Fundamentals (AZ-900)

Microsoft | July 2023

Google Cloud Introduction to Generative AI

Google | June 2023

Certified Data Science Practitioner (DSP-110)

Certnexus | May 2021

Certified Task Manager

Arcadis Flagship Program | Nov 2020

Scrum Certified Product Owner (CSPO)

Scrum Alliance | Oct 2017

Blogs



Generative AI Blogs (30)

Data Science Blogs (41)

Financial Analysis Using Python (19)

Geospatial Analysis Using Python (4)

App Development Using Python (16)

Skills


Programming Languages & Tools


Python
R
GitHub
Docker

Azure ML Studio
Azure DevOps
Power BI
Plotly | Dash









Product Prototypes

R Shiny Project Management APP

Github | R
The app built using R shiny lets users track their projects, tasks, generate visuals and Gantt charts instantly. The UI was built like MS Excel with frequently used operations enabled on web such as pivot, auto fill etc.

Crash Analyser App

Github | R
A crash analyser app built with R shiny lets user load the data, carry exploratory data analysis and visualize the trends in an interactive mode.

Classification Model Simulator App

Github | Python
A simulator build in python which lets user build model and view resulting metrics in a interactive mode. It Lets user build & experiment multiple models and compare their performances.

Product Price Optimizer App

Github | Python
The Price optimization app built in python helps businesses strike the right balance of efficient pricing, achieving profit objectives, and also serve their customers.

Customer Loyalty Program App

Github | Python
The app built using python-Dash helps business to segment their customers into various categories to help businesses make data-driven decisions to improve customer loyalty..

Customer Lifetime Value App

Github | Python
The app built in python helps measure the Customer Lifetime Value which is the profit that a business will make from a specific customer over the period of their association with the business.

Scientific Article classification

Github | Python
A multilabel text classification model built with fastai classifies the scientific articles by giving token of identification to research articles which facilitates recommendation and search process.

Auto ML in Power BI

Github | Python
Leveraging the power of auto ML and simplicity of Power BI to create a user-friendly dashboard for data insights. Used PyCaret library for model building and designed a dashboard where the model performance can be measured and visualized.

Trainee Performance Evaluation

Github | R
A model to enabling client to strengthen its training program by figuring out of the most important factors that lead to better engagement and performance of trainee.

R Shiny App for Interactive Model Building

Github | R
R Shiny App for data exploration, interactive model building, identifying variable importance and predicting on test data.

Predicting Hospitalization Duration

Github | Python
The model can help hospitals to identify patients of high LOS risk at the time of admission. Once identified, their treatment plan can be optimized to minimize LOS, lower the chance of staff/visitor infection, better room and bed allocation planning.

Simulation Modelling in Python

Github | Python
A python app for simulating the probability of pipe failure. The simulated results would help businesses to decide on whether to continue with the current design or to review and redesign the pipe.









Awards & Recognitions