Sai Teja K has over 2 years of experience in mentoring team members, performing code reviews, and conducting technical queries solving sessions. Some of their skills and experiences include developing ETL data pipelines and machine learning models in Python, performing data analysis and visualization in Tableau, and working with big data technologies like Spark, Hadoop, and AWS. They have a Master's in Data Analytics from Clark University and were a Business Technology Solutions Associate at ZS Associates.

1. Sai Teja K
+1-774-253-9819
ksaiteja1003@gmail.com
https://www.linkedin.com/in/ksaiteja1003/
https://github.com/ksaiteja1003
PROFESSIONAL SUMMARY
• 2+ years of experience in mentoring 2 team members, performing code reviews in Python & conducting
technical queries solving sessions.
• Designed and developed a mastering solution for the Pharma Industry for Trials, Sites, and Investigators and
increasing data accuracy by 85% by using TAMR MDM Tool.
• Collaborated with 2+ client stakeholders to gather requirements and ensured accurate implementation of client
business needs for specific KPI's.
• Developed ETL data pipelines for 5 data sources of oncology clinical trials study data reducing the processing
time by 35% and engineered them using AWS, PySpark, and Apache Airflow into a single scalable repository
for further research and analysis.
• Experience in managing data-related requests from clients, analyzing issues, and providing efficient resolution
within 24 hours.
• Mined and identified trends in Healthcare data sets to help clients make informed decisions, resulting in a
Client Delight Award.
• Created data testing scenarios in the application to ensure data accuracy and completeness.
• Provided inputs and support to senior team members for the project implementation plans.
SKILLS
• Languages: Python, MySQL
• Tools: Microsoft Office(Excel, Word, PPT),
Tableau, TAMR MDM, Zeppelin, Jupyter
• Libraries: NumPy, Pandas, Matplotlib,
Seaborn, Sklearn
• Machine Learning: Supervised(Regression,
Classification) & Unsupervised
• Big Data Technologies: PySpark, Hadoop,
MapReduce, Apache HBase, Sqoop, Flume,
Hive.
• Cloud Computing: AWS - S3, ATHENA, EC2,
EMR, REDSHIFT, AIRFLOW
• Version Controlling: Jira, Bitbucket
EDUCATION
Master in Data Analytics
Clark University
Graduation: August-2023
PG Diploma in Data Science Engineering
Great Lakes Executive Learning
Bachelor of Technology in ECE
SRM Institute of Science and Technology
PROFESSIONAL EXPERIENCE
Business Technology Solutions Associate
ZS Associates (Feb’21 – Aug’22)
Business Technology Analyst Intern
ZS Associates (Aug’20 – Jan’21)
ACHIEVEMENTS
• Client Delight Award by ZS Associates.
• Participated in Trekking in the Himalayas
(Bramhatal).

2. PROJECTS
Aspiring Mind(AMCAT) Employees Salary Prediction
AMCAT is a test that's conducted for graduates to test their domain skills and various personal traits. AMCAT
has collected around 200K records of employees who have appeared for the test and their education and location
details. Based on that we have to predict their salary per year.
Key skills: Data Pre-processing, Exploratory Data Analysis, Machine Learning- Regression using Python, Model
Evaluation, Hyper Parameter Tuning.
Contribution:
Ø Performed extensive coding and data preprocessing of 200K data points using Python, resulting in
improved accuracy of predictions by 15%.
Ø Implemented a Machine Learning pipeline for prediction of salary of employed professionals with 87%
accuracy by hyperparameter tuning of a Machine Learning-Regression model.
Feasibility Intelligence and Design Optimizer (FIDO)
FIDO De-duplicates various data sources and provides insightful analytics for decision-making throughout the
clinical trial planning process including site & investigator feasibility to break a long chain of clinical trial
inefficiencies that delay progress, burden participants, limit trial diversity and drain funding for research and
discovery.
Key skills: Healthcare Analytics
Contribution:
Ø Extensively worked on Data wrangling and proposed solutions for cleaning the data using PySpark,
MySQL, and Python.
Ø Performed counterfactual analysis to fill in for missing values using Python, resulting in an improvement
of KPI Enrollment Duration by 5%.
Ø Prepared data visualization and reports using Tableau for visualization of clinical trials timeline.
Ø Designed a method for standardizing the 300K variations of 27K diseases for multiple data sources
leveraging different ontologies using TERMite and CENTREE which resulted in an increase of data
accuracy of diseases by 60%.
Ø Analyzed key performance indicators to understand the enrollment of patients, including enrollment
duration, number of patients enrolled.
Ø Corrected the mapping of Therapeutic Area to disease for 5 data sources, resulting in 100% accuracy of
mapping.
IMDB Top 250 Movies data pipeline
IMDB is an online database of information about movies, television shows, video games, and streaming services
and In this project, Apache Airflow was used to build a data pipeline for extracting the top 250 IMDB movies by
rating by web scrapping.
Key skills: Apache Airflow, Web scrapping using Python.
Contribution:
Ø Development of web scrapper that extracts information of top 250 movies from the IMDB website
using Python and derive conclusions of what movie was most profitable.