Harshit Awasthi
4 yrs 7 mos
Associate Data Engineer
Quaero
Immediate
NIT Agartala
Summary
Hands-on experience in working with distributed large datasets using SQL Server, Hive, SnowFlake, Python and ML algorithms for predictive modelling.
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Skills
3 - 5 yrs
Excel Dashboard
1 - 3 yrs
ETL
Feature Selection
Hive
Jupyter Notebook
Linear Regression
Logistic Regression
Missing Value Treatment
MS SQL
pandas
Python
Random Forest
scikit-learn
Snowflake
SQL
Statistical Analysis
Tableau
Tree Based Models
Career Journey (4 yrs 7 mos)
Associate Data Engineer
Quaero
Jan 2019 - Present
2 yrs 1 mo
Projects (2)
Description: 
  • ESPN Fantasy App Acquisition Model
Given the behaviour of users on the ESPN website, that included content affinity, browsing history & fan preference, predict the likelihood of users to download the Fantasy Premier League mobile
application. The results were used to drive campaigns targeted at acquiring users for the mobile app every season. It included the following techniques -
  1. Data aggregation to create signals
  2. Feature engineering to create >60 input features
  3. Training a random forest in pySpark using MLLib
  • Worked on Quaero CDP (A PaaS product for managing first-party data) for creating Aggregation and Transformation workflows for transforming incoming data from multiple sources.
  • Worked on ESPN AdScope and Fan Relationship Management project to create data pipeline ingesting data from different data sources such as website click-stream, Google Double click Ad Impressions and Mobile App Subscriptions then processing data using workflows for client-facing deliverable data on SnowFlake.
  • Built standard queries to ensure data quality & data cleaning and identifying data gaps & inconsistencies.
  • Understanding the whole data flow from GCP to Snowflake and building the workflows for effective data processing.
  • Developed automated reports for daily load monitoring using SQL Server and designed client-facing reports and dashboards using Looker software.
Worked as Associate Data Engineer on ESPN AdScope project
Skills
Statistical Analysis
scikit-learn
Missing Value Treatment
Hive
Feature Selection
Python
Tree Based Models
pandas
Tableau
Logistic Regression
ETL
SQL
MS SQL
Snowflake
Linear Regression
Random Forest
Jupyter Notebook
Company Stage
Growth
Company Type
Product
Company Size
51-200
Company Location
Bengaluru, Karnātaka, India
Team Role
Team Member
Team Size
5
B2B/B2C
Business (B2B)
Sector Learning
Fantasy Sports, Enterprise SaaS
Switch Reasons (1)
Wanted new challenges

PROJECTS (2)
AdScope Migration-ESPN
Mar 2019 - Sep 2019
6 mos
Problem/Context
The old ESPN AdScope data pipeline was based on Netezza which was slow. The Target was to implement a new data pipeline for all AdScope data to new data pipeline to SnowFlake using Quaero CDP(A SaaS product for managing first-party data)
Solution/What you did
Worked in ESPN AdScope project ingesting data from different data sources like SFTP, GCS, GAM then processing data using custom workflows for client-facing deliverable data on SnowFlake.
Built standard queries to ensure data quality & data cleaning and identifying data gaps &
inconsistencies.
Developed automated reports for daily load monitoring using SQL Server and designed client-facing reports and dashboards using Looker software
Business Impact
Data processing time is reduced to a significant amount.
Skills (5)
MS SQL
SQL
Python
Snowflake
Hive
Sector Learning
Enterprise SaaS, Software
B2B/B2C
Business (B2B)
Team Role
Team Member
Team Size
5
ESPN Fantasy App Acquisition Model
Mar 2020 - Apr 2020
1 mo
Problem/Context
Given the behaviour of users on the ESPN website, that included content affinity, browsing history & fan preference, predict the likelihood of users to download the Fantasy Premier League mobile
application. The results were used to drive campaigns targeted at acquiring users for the mobile app every season.
Solution/What you did
1. Data aggregation to create signals
2. Feature engineering to create >60 input features
3. Training a random forest in pySpark using MLLib
Business Impact
Targeted campaigns can be launched using customer behaviour.
Skills (5)
Python
Tree Based Models
SQL
Random Forest
Feature Selection
Sector Learning
Fantasy Sports
B2B/B2C
Business (B2B)
Team Role
Team Member
Team Size
5
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Engineer
Vedanta Resources
Jun 2017 - Dec 2019
2 yrs 6 mos
Description: 
  • Strategic planning for electrical installations so as to support underground mines development-heavy machinery power supply units, ventilation and de-watering electrical units.
  • Interacting with different departments for executing the maintenance of equipment and enhancing the overall efficiency.
  • Monitored and analysed the data of process parameters of roaster plant in order to increase the performance of wet gas precipitator and reduce the downtime using Excel.
Worked as Electrical Engineer in project management team
Skills
Excel Dashboard
Company Stage
Late
Company Type
Product
Company Size
1001-5000
Company Location
Udaipur, Rājasthān, India
Team Role
Individual Contributor
Team Size
2
B2B/B2C
Business (B2B)
Sector Learning
Metals and Mining
Switch Reasons (1)
Change of strategy/roadmap

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NIT Agartala
Electrical Engineering
Jun 2013 - May 2017
3 yrs 11 mos

B.Tech in Electrical Engineering
Specialization
Degree: Electrical Engineering
Category: Electrical Engineering
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More
Certificates (3)
SQL for Data Analysis and Business IntelligencePython for Data Science and Machine LearningTableau 2020 A-Z: Hands-on Tableau Training For Data Science
Personality
Success Statement
I am motivated by Knowledge and Financial Security, I work in Cautious and Spontaneous ways, and my ideal work allows forWorking with facts and New Solutions
Life Priority
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Security
Feeling secure is a basic human need, and right now financial stability is top of mind. Creating a backup plan and getting financial advice from an expert can be steps on the path to stability.
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Involvement
Participating with sense of belonging is an important characteristic. Having legitimate voice in decision making can fulfill the craving for involvement.
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Fame
Building a professional platform based on unique personal attributes is front and center. Becoming well known involves taking some risks, so finding a way to be the center of attention can be small step toward ambitious vision.