Machine Learning Business Analyst

Reema Syeda

****.*@************.*** +1-857-***-**** Boston-MA LinkedIn

EDUCATION

Northeastern University Boston, MA - Master of Science in Information Systems Sep 2024 - Present Relevant Coursework: Application Engineering and Development, Advanced Business Process and Engineering, Database Management and Database Design, Managing Operational Risk for Engineers, Agile Software Development Reva University Bangalore, IN - Bachelor of Engineering in Computer Science and Information Technology Jun 2020 – Jun 2024 Relevant Coursework: Algorithm Design, Python, Database Management, Computer Organization, Software Engineering, Artificial Intelligence and Machine Learning, Compilers, Object Oriented Programming, Operating Systems, Unix Programming SKILLS

Technical Skills: Python, Java, JavaScript, HTML/CSS, React.js, Spring Boot, Express.js, MySQL, MongoDB, Snowflake, Tableau, Power BI, Google Analytics, Lucidchart, Figma, MS Visio, Trello, AWS (S3, EC2, Lambda), Azure Data Factory, Amazon Web Services, Google Cloud Business Skills: Jira, Confluence, Agile Methodologies (Scrum/Kanban), Miro, Strategic Planning, Product Management PROFESSIONAL EXPERIENCE

Product & Business Analyst Intern DONOR MONEY, BANGALORE, IN Mar 2024 – Jul 2024 Donor Money Platform (Fintech – Digital Currency)

• Collaborated with engineering and cross-functional teams to define and refine product requirements, building sprint goals, and prioritizing features that improved donor conversion by 18% over 2 months.

• Designed and implemented structured A/B testing processes for new features, using SQL and Power BI to analyse performance metrics and inform iterative development cycles.

• Created and maintained comprehensive product documentation using Confluence, enhancing onboarding speed for new team members and reducing dependency on PMs by 30%.

• Created functional specifications, mapped business requirements into roadmaps, and managed sprint delivery in Jira. Full Stack Developer Intern KEYSTRIDE TECHNOLOGIES, BANGALORE, IN Jul 2023 – Sep 2023 US – Based Dental Client Site

• Engineered responsive, modular front-end interfaces using JavaScript, HTML/CSS, and React components that reduced page load times by 40% and improved UI accessibility across mobile devices.

• Integrated secure REST APIs and implemented robust error-handling logic for backend operations using Node.js and MongoDB, enhancing system reliability in high-traffic user scenarios.

• Deployed full-stack applications on AWS with CI/CD pipelines using GitHub and Docker, reducing deployment friction and enabling fast rollbacks during QA testing cycles.

• Automated deployment workflows using GitHub Actions and Dockerised environments on AWS EC2, resulting in a 60% reduction in deployment time and enabling rollback within 90 seconds during test failures. RELEVANT PROJECTS

Business Operations Dashboard Stakeholder Management + LucidChart + Tableau + Excel Sep 2024 – Dec 2024

• Designed a comprehensive KPI dashboard using Tableau and Excel to monitor simulated operational performance across 50+ tickets, measuring resolution time, agent productivity, and service quality metrics.

• Mapped the "As-Is" vs. "To-Be" service desk workflows in Lucidchart as part of a service process re-engineering project. The visual models highlighted gaps in escalation paths, duplicated efforts, and lack of clarity in agent triage responsibilities.

• This redesign effort resulted in a proposed workflow that cut down triage-to-assignment time and improved queue management—leading to an estimated 20% gain in first-response time and a 15% reduction in overall ticket lifecycle duration.Used Lucid chart to visualize current vs. ideal state workflows, offering recommendations for IT-driven process improvements. Smart India Hackathon - Disaster Management Dashboard Java + MySQL + Aws Jun 2024 - Jul 2024

• Selected among Top 10 teams across India in the nationwide Smart India Hackathon for building an AI-enabled disaster management dashboard under national evaluation.

• Designed and deployed a scalable web-based system to centralize emergency response data using Java for backend logic, MySQL for structured incident storage, and AWS (EC2/S3) for cloud hosting.

• Collaborated with UI designers to create an intuitive interface for first responders, optimizing user flows under time-sensitive conditions. AI Roadmap for a Language Learning App Market Analysis + User Research + Product Strategy + NLP Jun 2024 - Jul 2024

• Proposed a 6-month AI roadmap for a Duolingo-style app, incorporating NLP techniques like sentence embedding, sentiment analysis, and topic modeling to tailor learning experiences based on user proficiency and behavior.

• Defined sprint-level milestones for three AI features: (1) grammar correction API integration, (2) reinforcement prompt personalization using intent detection, and (3) tone-aware feedback generation.

• Developed a KPI framework aligned with business goals: projected 20% improvement in daily active users (DAUs), 15% churn reduction, and 25% increase in average session duration over 3 months post-launch.

• Created user flow diagrams and AI feature specs using Figma and Notion to support alignment across product, UX, and data science teams. CERTIFICATIONS

Microsoft Azure Cloud Fundamentals (AZ-900) – Sep 2021, Amazon Web Services (AWS) CLF CO2 – Feb 2024, Certified Scrum Master(CSM)- Mar 2024 Microsoft Azure Data Fundamentals – Sep 2021, Microsoft Azure AI Fundamentals – Oct 2021, Microsoft Azure Solutions Architect (AZ-305) – In Progress Lean Six Sigma – In Progress

PUBLICATIONS

S. K. S, S. T. Ahmed, A. S. Fathima and S. Reema, "An Improved System for Students Feedback Analysis Using Supervised Probability Techniques," 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), Gautam Buddha Nagar, India, 2023, pp. 328-333, doi: 10.1109/UPCON59197.2023.10434859 URL : https://ieeexplore.ieee.org/document/10434859 Syeda Reema, Syed Thouheed Ahmed, & Konjengbam Dollar S. (2023). Examining the Effectiveness of AR/VR Technologies in Medical Training and Surgical Simulations . Milestone Transactions on Medical Technometrics, 1(1), 37–44. URL : https://doi.org/10.5281/zenodo.8268752

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