Sabarish Subramaniam
Teaching Assistant @D\'amore-Mckim School Of Business At Northeastern University
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WORK HISTORY
Teaching Assistant @D\'amore-Mckim School Of Business At Northeastern University
Boston, MA, US
Graduate Teaching Assistant for MKTG6234 - Marketing Analytics under Professor Kim Seung Hyun at the D\'Amore-McKim School of Business, Northeastern University
EDUCATION
Anna University
Bachelor of Engineering
Northeastern University
Master of Science - MS
ABOUT SABARISH SUBRAMANIAM
I am currently pursuing a Master’s in Data Analytics and Engineering at Northeastern University, with 2.5 years of hands-on experience spanning Data Analytics, Data Engineering, and Data Science. My expertise lies in handling large and intricate datasets, uncovering insights, and enabling data-driven decision-making to drive business success. With a strong analytical mindset and a passion for solving complex problems, I specialize in transforming raw data into actionable strategies. By leveraging advanced analytics and engineering techniques, I aim to optimize processes, enhance efficiency, and contribute to impactful business solutions. Constantly driven by curiosity and a commitment to excellence, I stay at the forefront of data innovation, ready to make a meaningful impact in the ever-evolving analytics landscape. Technical Skills: Programming & Scripting : Python, R, Structured Query Language (SQL), Git. Libraries & Framework : Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, NLTK, TensorFlow, Keras. Database & Business Intelligence : Snowflake, Relational Database (MySQL, PostgreSQL), NoSQL (Mongo DB), Data cleaning, Data Migration. Data Pipelines & Orchestration: Data Build Tool (dbt), PySpark, Databricks, Apache Airflow, Tableau Prep, ETL/ELT, Data Modeling. Cloud: AWS (Redshift, S3, Glue ETL, Athena), Google Cloud Platform (GCP Composer, BigQuery), Azure (Data Lake, Data Factory, Synapse). Data Visualization Tools : Tableau, Microsoft Power BI, AWS QuickSight, GCP Looker. Machine Learning & Statistics : Linear Regression, Logistic Regression, Classification Models, Statistical Analysis and Predictive Modeling. Other Tools : Microsoft Office Suite (MS Excel – VLOOKUP, Pivot Tables | Word | PowerPoint), Google Spreadsheets, JIRA, Confluence. Contact : s••••••••@gmail.com
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