Abhishek Mattihalli
abhimattihalli9707@gmail.com | www.linkedin.com/in/abhishek-m-14aa41115 | +91-9108057059 | Bengaluru
Education
Manipal Institute of Technology (MIT) Manipal, India
Master of Engineering, Big Data Analytics Aug 2021 - Jul 2023
G M Institute of Technology Karnataka, India
Engineering, Electronics and Communication Aug 2016 - Jul 2020
Technical Skills
Languages: Python, SQL, R, C/C++
Data Science Technologies: Expertise in Probability & Statistics, Time Series Forecasting, In-depth knowledge of
Supervised/Unsupervised/Reinforcement Learning
ETL tools : Apache Spark, Apache Hadoop, Azure Data Bricks, Azure Data Factory, RapidMIner, KnowledgeStudio
Data Visualization: PowerBI, Tableau, Panopticon
Tools & Technologies: Linux, Git, Docker, Kubernetes, Hadoop,Jupyter
Experience
Jr Data Scientist Aug 2022 – Present
Altair Engineering Ltd Bengaluru, India
• Spearheaded predictive and prescriptive analytics initiatives for automotive, manufacturing, and marketing sectors
• Innovated and implemented a robust machine learning system predicting structural responses and validating new
designs.
• Conducted compelling pre-sales demonstrations to prospective clients.
Student Research Assistant Oct 2021 – Jul 2022
AIML Lab, MSIS (Manipal University) Manipal, India
• Automated vehicle number plate detection and recognition through cutting-edge computer vision techniques.
• Crafted a sophisticated recommendation system for online shopping websites and conducted sentiment analysis on
Twitter data using NLP.
• Employed machine learning to extract and analyze text from bills and invoices, contributing to in-depth statistical
analysis.
Data Engineer Intern Jan 2021 – Jun 2021
Ahana systems and solutions Bengaluru, India
• Designed and created database structures to efficiently store and organize data.
• Recognized as a great team player while working in areas such as developing and managing the SQL database.
• Identified and deployed improvements for company data management systems performing necessary data abstraction
and data acquisition tasks
Telematics Engineer Sept 2020 – Dec 2020
Harman International Bengaluru, India
• Orchestrated 5G Platform initiatives, encompassing diverse spectrum types (low, mid, high) and deployment models.
• Utilized a network simulator to model network behavior, calculating interactions among entities such as routers, nodes,
access points, and links.
• Led the eCall initiative, deploying a device in vehicles to automatically dial emergency services following road
accidents.
Certifications
• RapidMiner Data Engineering – Professional Certification
• Probability Statistics for Machine Learning Data Science
• Applications Use Cases Professional Certification
• Probability Theory, Statistics and Exploratory Data Analysis
• Use Power Bi for Financial Data Analysis
• Fundamentals of visualization with Tableau
• Guided project on Scheduling Selenium TestNG tests via JENKINS CI/CD tool
Projects
Predictive Modelling for Headlamp Leveling Test
∗ Developed a predictive model for Head Lamp Test output, addressing regulatory compliance through the application
of advanced data analytics.
∗ Applied ML regression and classification models to the historical data with an accuracy of 97.4%, showcasing
proficiency in model training and selection for optimal performance.
∗ Orchestrated the seamless integration of multiple data sources, including APIs, Excel, CSVs, and JSON.
∗ Applied the CRISP DM process (Cross Industry Standard Process for Data Mining) in all stages of data analytics
consulting projects, ensuring a strategic and structured approach to problem-solving.
∗ Trained ML models can be exported as Python scripts which facilitates scoring new custom data against the model
and exporting results to a CSV file.
∗ Conducted three-day client training sessions showcasing compelling demonstrations of Data Insights and ML Model
operational capabilities along with effective data visualization techniques, emphasizing strong communication and
presentation skills.
Scaling AI/ML Data Needs: Migrating On-Premise Data Engineering Workloads to Azure Cloud
∗ Spearheaded the development of a comprehensive Azure-based data platform, encompassing data ingestion,
transformation, loading, and reporting.
∗ Leveraged cutting-edge tools such as Azure Data Factory, Data Lake Storage Gen2, Databricks, Synapse Analytics,
Key Vault, Active Directory, and Power BI for seamless integration and optimal data flow.
∗ Executed a high-impact use case involving the extraction of on-premise SQL Server database tables through Azure
Data Factory, subsequent storage in Azure Data Lake, transformation via Azure Databricks, loading into Azure
Synapse Analytics, and concluding with interactive dashboard creation in Microsoft Power BI.
∗ Implemented robust monitoring and governance mechanisms utilizing Azure Active Directory (AAD) and Azure Key
Vault, ensuring security, compliance, and efficient oversight throughout the data engineering project lifecycle.
Elevating Sales Projections through Time Series Forecasting and Text Extraction
∗ Proven experience in leveraging Python to automate the extraction and processing of structured and unstructured
data from diverse invoice formats, including paper, email.
∗ Applied Time series analysis and advanced statistical methods, specifically ARIMA models, to derive insightful
conclusions and forecast future values across diverse datasets, encompassing economic indicators,ROI,GMV, etc.
∗ Demonstrated adeptness in utilizing pivotal Python libraries such as Pytesseract, Textract, Pandas, Tabula, Camelot,
OpenCV, and Pillow for the efficient extraction of data from invoices and implementing data preprocessing
techniques, including handling missing values, aggregating data, and utilizing libraries such as NumPy, Pandas, and
Matplotlib to elevate data quality.
∗ Experienced in normalizing data, cleaning text, validating data quality, and employing data augmentation to enhance
accuracy and reliability, expertise in parameter selection, employing a grid search approach for fine-tuning ARIMA
and Time Series models.
