Data Analyst Business

Nikita Priyadarshini Das

******.******@*****.*** 865-***-**** 824-***-**** Bhubaneswar, Odisha

Career Objective : Results-driven expert with more than 2.5+ years’ experience in the IT industry as a Technical Business Analyst with a proven track record of increasing business value via information analysis/data analysis. Seeking a challenging position as a Data Analyst to utilise my analytical & technical skills to solve complex business problems.

Education

● B.Tech, Information Technology (IT),

VSSUT Burla(2016-2020)

CGPA= 7.78/10

● Class XII, CBSE: 86.4%(2015)

● Class X, CBSE: 10 CGPA (2013)

Certificates

● CCE-IIT Madras, Advanced Certification

in DataScience & AI

● Google Cloud Platform, Associate

Engineer (GCP ACE)

Skills

● Expertise in Python, SQL, Excel,Power

BI, Ietc

● Cloud Expertise: GCP

● Proficient in OS platforms:

Windows/Linux

● Data engineering and analytics: SQL,

Database management, pandas,

numpy, matplotlib, seaborn, GCP

BigQuery, etc

● Agile Methodologies, gap analysis,

market research,BRD, Project

management, Stakeholder

management, Meeting facilitation

● Google Analytics

● Hands-on experience working with

Stat ML algorithms: Linear Regression,

Logistic Regression, Decision Tree,

Random Forest, XGBoost, Clustering

● Database: BigQuery, PostgreSQL

● Managing high octane client

engagements

● Strong Research and analytical skills.

Work Experience

Quantiphi Analytics

Business Analyst, GCP Pre-sales and GTM, February 2022- Present

● Development of revenue planning dashboards

Leveraging the structured sales data(revenue, targets, pipedrive reports,etc) to create visualisation and interactive dashboards to strategise GTM activities, and formulate quarterly/annual revenue targets

Worked on using the raw data to generate graphs, charts, and other required visuals to create pitch decks for sales planning and strategy development sessions

● Handled the TMEG, Retail and BFSI portfolio

Spearheaded the pre-sales activities to strengthen the partner ecosystem for generating new leads and customer opportunities

Worked with Google FSR and Customer Engineers to ideate and develop solutions, client pitch decks, etc

Worked on scoping out solutions for various Media and entertainment, Retail and BFSI clients

Evaluating business processes, anticipating requirements, uncovering areas for improvement, and developing and implementing solutions

Leading ongoing reviews of business processes and developing optimization strategies. Conducting meetings and presentations to share ideas and findings

Performed GAP analysis for new requirements while organising project statuses based on levels of priority and importance

● Sales Data Analytics

Worked as a data analyst to perform extensive EDA on sales data multinational food processing company to identify the different categories of their products, understand consumption patterns varying based on different regions of stores and SKUs

Created an extensive EDA report for the customer and the data science team to build out ML models on top of it

● Ecommerce web data analytics on GCP

Leverage the data on GCP BigQuery for Ad performance analytics for a time window of three months to compute key metrics like ROAS and CTR metrics for advertisers

Customer Segmentation and targeting: Implemented RFM(recency, frequency, monetary)frameworks to identify high value customers and optimise marketing campaigns and customer retention strategies

● Domain understanding of TMEG

solutions along with BFSI and Retail

solutions.

● Strong business acumen;Sales Strategy

and Planning, customer success

Workshops & Activities

● Attended a workshop on the Internet of

things (IoT) to understand the

possibilities and opportunities of using

IoT data in production systems

● Chief Editor, Literary Society

e-newspaper: VISSION

● Co-ordinated multiple events in the

Vassaunt Cultural Fests and tech Fests

Accenture

SAP MM Consultant, January 2021- February 2022

● Customising and managing SAP Frameworks

Managing end-to-end SAP Material management for a state-owned oil company of the United Arab Emirates

Working jointly with the client stakeholders to brainstorm around design/implementation roadmap, modify framework and system modules to resolve client queries and tickets

Experienced in User Acceptance Testing (UAT)

Involved in preparing BRD, FRD and SRS.

Center for Development of Advanced Computing (CDAC), Pune Computer Science Intern (December 2018 - January 2019)

Extensive research on High-performance computing and Deep Learning techniques to accelerate R&D activities in college

Conducted workshops and presentations to showcase the capability of HPC in accelerating Deep Learning deployment frameworks Projects

● Descriptive analysis on simulated B2C data

This project involved creation of simulated mock datasets for sales, customer and product level information; analysis of the interlinked relations across the tables

Involved complex querying and analysis to identify KPIs of gold customers, specific products and regions based on sales data

● Recommendation Engine using Netflix dataset

Leveraging open source available datasets: user data set(containing user specific information) and movie dataset(movie specific information)

Involved basic EDA to understand the data sets, underlying patterns and signals across the datasets

Developed a baseline recommendation system to recommend top N movies to users based on their profile information

● Time Series Forecasting on AirPassengers data:

Implemented time series forecasting models(like ARIMA) to predict the passenger count for the upcoming 5 years time horizon based on historical data spanning across 1949 to 1960

This involved various data preprocessing techniques to transform the data into a consumable format to be fed into a time series forecasting model

● ML-based Heart Disease Prediction algorithm

Leveraging publicly available datasets to develop multiple ML models using supervised and unsupervised ML techniques. Experimented with multiple traditional ML Algorithms ( Xg Boost, Random Forest, Decision Tree, etc), and Deep Learning techniques to evaluate performance metrics

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