SHIVAM MISHRA
With 4 years of experience at BlackRock, Ericsson, and Rocket Mortgage, and a Master’s in Data Science from Indiana University, I have extensive experience in data analysis and visualization, utilizing tools like Tableau, Power BI, and matplotlib to create actionable insights and clear, impactful visual representations of complex data. Additionally, I have developed and optimized ETL pipelines, automated data ingestion processes, and improved data query efficiency, resulting in significant cost savings and operational improvements.
Experience
Research Assistant . Bloomington . Indiana
• Conducted a comprehensive overhaul and analysis of datasets exceeding 1 terabyte, uncovering pivotal insights thatredefined research approaches and led to a notable 30% increase in operational efficiency.
• Spearheaded the design and deployment of over 10 sophisticated Tableau dashboards, catalyzing a 40% increase in decisionmaking efficiency and bolstering cross-departmental collaboration with impactful, real-time data visualizations.
Data Engineer Intern . Detroit . Michigan
• Engineered and optimized ETL pipelines using AWS Glue, PySpark achieving cost savings of $10,000 and adeptly handling datasets exceeding 5 terabytes. • Processed and analyzed over 5 TB of customer data with PySpark, driving insights through Tableau dashboards. • Engineered robust CI/CD pipelines utilizing Jenkins, CircleCI, and Git to automate and ensure the reliability of job deployments.
Research Assistant . Bloomington . Indiana
• Crafted and deployed Python data wrangling scripts to extract over 3 terabytes of insurance data from various online sources, integrating seamlessly with Snowflake. • Executed meticulous data operations, encompassing the cleaning, aggregating, transforming, and visualizing of over 2 million data points from multiple health insurers, significantly enhancing research precision and operational workflow.
Data Analyst . Bangalore . Inida
• Analyzed terabytes of production data using PySpark and SQL identifying errors, trends, and patterns in network reports, resulting in a 12% reduction in data errors.
• Optimized Jenkins pipeline stages for build, test, and deploy in CI/CD processes for open-source projects, including Kube State Metrics, improving product reliability and driving a 16% increase in the user base.
• Engineered Python validation scripts to validate thousands JSON and YAML files uploaded by users, preventing code failures in internal Kubernetes projects and reducing failure rates by 80%.
Data Analyst . Mumbai . Inida
• Collaborated with Aladdin stakeholders to gather essential business requirements, ensuring a deep understanding of
data needs and crafting effective business solutions for Aladdin clients.
• Developed Tableau dashboards for real-time compute farm resource visualization, increasing resource management
efficiency by 25% and reducing report generation time.
• Crafted a Python and SQL-based file monitoring tool to streamline data handling from various index vendors, achieving a 60% increase in process efficiency.
• Utilized Spark and SQL for in-depth analysis of production errors in client reports, achieving a 40% reduction in data discrepancies and significantly boosting data quality and reliability.
Academic Projects
Stocks Recommendation System
1. Predictive analysis of stock prices using ARIMA and LSTM models.
2. Sentiment analysis using VADER on social media and news data.
3. Web-based platform for insightful stock investment decisions.
Netflix Analysis on Tableau
1. Developed a comprehensive dashboard for Netflix movies and TV shows, featuring a range of metrics and detailed information.
2. This dashboard is designed to provide an insightful overview of content trends, viewer preferences, and other key data points.
A Machine Learning Assisted Optical Network
1. Increased high volumes of traffic demands at datacenters are handled by all-optical Multistage Interconnection Networks (MIN) which are implicitly designed to withstand the same.
2. Analyzed Contention resolution mechanism in MINs which becomes a bottleneck to handle such data traffic.
3. Electronic signal processing methods which are traditionally used to resolve contention in MIN is replaced with a
select list of machine learning algorithms for contention resolution in this paper.
4. Examined Performance of the entire network in terms of injection rate, average latency by using Machine Learning
Algorithm and latency distribution is suitability accessed.
5. Co-Authored the paper on the same in ETRIJ Publication and submitted it for publication, Manuscript ID etrij-20210182, Jun 2021.
Education
Indiana Uiversity Bloomington . United States
Skills
- Programming languages: C, C++, Java, Perl, Python, JavaScript, SQL, Bash
- Libraries/Frameworks: Pandas, Scikit-learn, ReactJS, PySpark, PyTorch
- Databases/Cloud: MongoDB, Postgres, MySQL, Sybase, Cassandra, AWS S3, Glue ETL, Lambda, Route 53, Athena
- Miscellaneous: Tableau, Snowflake, Kubernetes, Docker, Hadoop, HTML, CSS
Badges
Certifications
Interests
I like reading books. Its like meditation for me. Some of my recommendations are:
I love cooking in my free time. I like to invent new dishes.
I love playing football since my 6th grade. I was in my school's and college's football team.
Awards & Certifications
- Finalists team of Grant Thornton idea case competition organized by Grant Thornton and Kelley school of Business.
- Best Project Based Learning Award for Smart Farming using IoT | Issued by VITC · Mar 2018
- Winners of IoT Makeathon V5.0Winners of IoT Makeathon V5.0
PBL(project based learning)awards are given by VIT Chennai to the projects with innovative ideas and good social and economic factors.
Issued by VITC- NOKIA · Mar 2018Issued by VITC- NOKIA · Mar 2018 IoT Makeathon is organized by School of Electronics And communication Engineering VITC every year to encourage students to come up with the best solutions of real Industrial problems. This was the 5 edition of the competition in association with NOKIA.