Data Analyst Machine Learning

Dixith Kumar Bandari

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Strategic and detail-oriented Data Analyst/Scien4st with 5+ years of experience in SQL, Python, Machine Learning, AI, Power BI, Tableau, and advanced data repor4ng. Skilled in Agile methodologies, business analysis, and self-service BI, with a proven ability to translate complex business needs into ac4onable, data-driven solu4ons through effec4ve cross-func4onal collabora4on. PROFESSIONAL EXPEREINCE

Data Scientist - ARCOOM LLC June 2024 – Present

• Executed full-cycle data science projects applying machine learning (classifica4on, regression, NLP, 4me series) and advanced sta4s4cal methods, achieving 25–40% improvements in model and forecas4ng precision using Python, TensorFlow, Py Torch, and scikit - learn.

• Designed and op4mized high-performance data pipelines and big data architectures with SQL, Py Spark, Airflow, and DBT, cuZng data processing 4mes by 35% and driving scalable analy4cs on GCP, Azure, u4lizing Snowflake, Big Query, Redshi_, and Synapse.

• Improved storage and repor4ng efficiency by 30% through Databricks-integrated solu4ons, building interac4ve dashboards in Tableau and enabling 20–30% faster decision-making through seamless cross-func4onal collabora4on and cloud-na4ve solu4ons. Data Scientist - Counsellors in the community association Feb 2024 – May 2025

• Led data-driven ini4a4ves for mobile applica4on development, integra4ng big data processing using Apache Spark and Hadoop, resul4ng in 40% faster data processing and enabling real-4me analy4cs within the CITCA mobile plaborm.

• Designed cloud-na4ve rela4onal databases and dynamic Power BI dashboards on AWS, improving repor4ng efficiency by 35% and enabling quicker data-driven decision-making for community programs and stakeholder presenta4ons.

• Conducted large-scale community surveys and sta4s4cal analyses, collec4ng and analyzing 10,000+ data points, contribu4ng to 25% more effec4ve resource alloca4on and delivering ac4onable insights that influenced program improvements and funding strategies. Data Analyst - NTT DATA (Connect Your Care) Dec 2020 – Dec 2022

• Performed end-to-end financial data analysis, live tracking in Salesforce, and IT support coordina4on, boos4ng issue resolu4on efficiency by 30% and automa4ng repor4ng processes through SQL-based ETL pipelines, improving data accuracy by 40% and cuZng manual efforts.

• Enhanced opera4onal decision-making by 25% through gap analysis, Power BI dashboards, and investment module development while establishing robust data quality prac4ces including metadata governance, data lineage, and standardized repor4ng across teams. Data Analyst - NTT DATA (SEI Investments) May 2019 – Nov 2020

• Led end-to-end business analysis by dra_ing BRDs, func4onal specs, SLAs, and use cases, reducing process inefficiencies by 30% through stakeholder alignment and JAD sessions, while driving strategic financial consul4ng with DAX and Power BI, improving repor4ng accuracy.

• Op4mized financial data pipelines and predic4ve analy4cs workflows, enhancing forecas4ng accuracy by 25% and enabling real-4me visibility into revenue, margins, and cost trends to support data-driven investment strategies. KEY ACHIEVEMENTS

• Strengthened organizaPonal outreach and community engagement, driving 35% growth in volunteer parPcipaPon and contribu4ng to 20% increased funding by leading recruitment ini4a4ves, organizing fundraising events, and fostering strong rela4onships with local government offices.

• Awarded “Best Employee” and client-recognized for driving 100% project conPnuity and boos4ng efficiency by 30% through independent leadership, strategic improvements, and high-impact soluPons during cri4cal opera4ons. EDUCATION

Master of Professional Studies - Data Science

UNIVERSITY OF MARYLAND BALTIMORE COUNTY - May 2024 Bachelor of Technology - Computer Science and Engineering MALLA REDDY COLLEGE OF ENGINEERING AND TECHNOLOGY – April 2019 TEECHNICAL SKILLS

Querying languages: MySQL, Oracle PLSQL, NoSQL, TSQL, MongoDB, PostgreSQL. VisualizaPon tools: Power BI, Tableau, SSRS, Jasperso_ Studio, Qlik Sense. Python packages: Pandas, Matplotlib, NumPy, Seaborn, Scikit-learn, Py-Torch, TensorFlow, Stats-Models, NLTK, Py-Spark, Fast API, SQL-Alchemy. Machine learning models: Linear Regression, Logis4c Regression, KNN, Decision Trees, Random Forest, Gradient Boos4ng Machines, Support Vector Machines, Naive Bayes, Neural Networks, K-means Clustering. Clouds and Data Warehouses: AWS, Azure, S3, GCP, Redshi_, Snowflake, Databricks, Big Query, Cloudera. Big Data tools: Hadoop, Hive, Spark, Kapa, HBase, Cassandra, Storm. CERTIFICATES

• Google Data Analyst – Coursera.

• Machine learning using Python – Coursera.

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