Prajakta Kulkarni Personal Details Prajakta Kulkarni Mobile: 510-309-7927 Email: prajakta.k.13@gmail.-com

LinkedIn: https://www.linkedin.-com/in/prajaktakc

Public Tableau: https://public.tableau.-com/profile/prajaktakc#!/

Skills : SQL, R, Python, Tableau, Kibana, Data Extraction, Data Preparation, Data Cleaning, Data Analysis, Data Segmentation, Big Data, MongoDB, Hadoop,Hive, ErWin, PostgreSQL, Elastic Search, JSON, Kafka, RESTAPI, Flink, Zepplin, Pivot tables.

Objective:

Looking for full time job opportunities in big data, data modeling and data visualization.

Course Work:

Relational DB Design and SQL Prog (30215) Data Modeling (2957) Big Data-Tools and Use Cases (30122) Data Analysis (30211) Dashboards and Data Visualization (30282) NoSQL Databases (30213) Python Programming (20776) Predictive Analytics(30331)

Experience:

WISRAN - Sunnyvale, CA Data Analyst (Dec 2016- Present) • Understanding and developing business use case, analyzing use case data. • Design and implement data pipeline using open source stack- kafka, flink, zepplin, hadoop and hive in aws. • Assist, own, research, deploy and configure technology solutions for data implementation. • Integral part of team throughout data analysis framework of defining the problem, collecting information,

data pre-processing, analysis and data visualization • Working on predictive and prescriptive analytics to deliver data driven solutions

MGM’s College of Engineering, India Research Assistant (2013 - 2015) • Worked on user oriented retrieval system based on interactive genetic algorithm • Taught undergraduates important concepts in software engineering • Developed tutorials on valuable software tools like Rational Rose

Academic Projects:Implementation of Recommendation System using Item-based Collaborative Filtering: (Oct 2016) • Built a personalized recommendation engine that suggests relevant movies to user based on movie rating. • Using IBCF algorithm available in R, extracted the user rating of each purchase associated with the item and

the rating is used as a weight. • Extracted the similarity of the item with each purchase associated with this item and identified the top 6

movie recommendations for users

Big Data solutions for automotive industry : (Sept 2016) • Data analysis for auto industry to improve decision making and supply chain using predictive analytics. • The recommendation was to apply the big data strategies to accelerate marketing campaign, target the new

customers and improve efficiency and supply chain capabilities to grow business in competitive auto sector. • Also highlighted key trends, architecture, recommended tech stack and deployment strategies.

Data System Architecture for location based services: (Aug 2016) • Designed an ERD and implemented a database using oracle to support location based service operations. • It keeps the list of commonly used names for places as an asset for map makers, location based services and

intelligence services. • Generate reports according to specifications for a company and its vendors.

• Market Segmentation Analysis for Cosmetic Market : (July2016) • Beauty industry is resistant to economic downtowns, raising per capita income accelerates beauty industry. • I have used tableau for visualizing the market trend and expenditure analysis in UK beauty industry. • The dashboard represents money spent on cosmetics for 2013 and 2014. • It contrasts year over year percentage change in spending on each product.

Education:

University of California, Santa Cruz (Silicon Valley Campus) Pursuing Certificate in Database and Data Analytics MGM's College of Engineering, India Master’s Degree in Computer Science Engineering (2015) Bachelor’s Degree in Computer Science Engineering (2012)