SAITEJUS SREEKANTH

Master's graduate specializing in data analytics and statistical modeling, with hands-on experience in cloud-based solutions. Proficient in Python, R, SQL, Tableau, and AWS, with a track record of developing predictive models and data pipelines. Demonstrated success in analyzing large datasets to provide actionable insights that enhance decision-making processes.

• Amazon Web Services Certified Cloud Practitioner certification
• Industrial IoT using machine learning
• 'Quality, Safety, and You' - NDIS Worker Orientation Module
• CHCCCS031 provide individualized support
• HLTWHS002 follow safe work practices for direct client care

Visa Status: Full-time work rights in Australia (Temporary Graduate 485 Visa, valid until 08/21/28)

• AI-ML image analysis, built and optimized an image processing pipeline to classify medical images on AWS EC2, improving deployment efficiency by 15%
• Telecom churn prediction built a machine learning model to forecast customer churn, improving prediction accuracy by 20%
• Cricket data analytics, automated data extraction, and analysis pipelines to visualize cricket match data, providing real-time insights for coaches and analysts
• Healthcare regression model created an OLS regression model to predict fatalities, achieving high accuracy and actionable insights for healthcare research
• Streamlit to analyze and visualize lab records, enabling faster data-driven decisions
• Low-cost ventilator using Arduino IOT Based Crop Protection and Irrigation System

• Analytical thinking and problem-solving: Apply statistical reasoning and critical thinking to uncover patterns, interpret complex datasets, and deliver actionable insights
• Data-Driven Decision Making: Use evidence-based analysis to recommend strategies that optimize business outcomes and improve operational efficiency.
• Technical Agility & Innovation: Quickly adapt to new tools, programming languages (e.g., Python, R, SQL), and emerging technologies to enhance data workflows and predictive models.
• Collaboration and cross-functional communication: Partner effectively with engineers, business stakeholders, and domain experts to translate technical findings into clear, impactful solutions
• Attention to Detail & Data Integrity: Maintain high data quality through rigorous validation, cleaning, and verification processes to ensure accuracy and reliability.
• Continuous Learning & Curiosity: Stay current with evolving data science trends, machine learning techniques, and AI applications to drive continuous improvement.
• Project ownership and accountability: manage end-to-end data projects, meeting deadlines, and delivering results with transparency and responsibility
• Business acumen and strategic insight: connect analytical results to real-world business needs, enabling data-informed decision-making, and measurable impact

• Football division championship medal
• School-level championship in volleyball and cricket
• Intra-school quiz competition runner-up