Mr. Mohamed Arsath J

Core data science & AI skills

• Machine Learning and Time Series Forecasting for demand planning, classification and regression problems.
• Python (Pandas, NumPy, OR-Tools) and SQL for data wrangling, modelling, optimization and production-ready analytics workflows.
• Business analytics – full lifecycle from problem framing, KPI definition and data modelling to dashboarding and decision support.

Big data & data platforms

• Hands-on experience with Big Data ecosystems including HiveQL, Apache Spark and PySpark for large-scale data processing and batch analytics.
• Data platform exposure to SnowflakeDB, MS SQL Server and star-schema data modelling for scalable, analytics-ready data warehouses.
• Tooling experience with RapidMiner, Power BI, Jupyter Notebook and Excel for EDA, visualization and experimentation.

Business & stakeholder skills

• Stakeholder management – works closely with global business users, supply chain planners and leadership teams to align analytics outcomes with business goals.
• Requirement gathering – converts high-level business questions into structured functional and technical specifications for data and ML solutions.
• Stakeholder communication – explains model outputs, scenarios and trade-offs in clear, business-friendly language for non-technical decision-makers.
• Gap analysis – identifies gaps in current reporting, planning and decision processes and designs analytics-driven workflows to address them.

AI S&OP Demand Planning – Global Petrochemical Manufacturer

• Engineered a multi-model forecasting system using XGBoost, ARIMA, Holt-Winters and Croston models, significantly improving forecast accuracy for global S&OP.
• Performed large-scale EDA on multi-year transaction data in Python, enhancing data quality and surfacing product and customer performance insights for planners.
• Designed RFM-based customer segmentation to inform targeted strategies and lifetime value (LTV) improvements.

Procurement & Supplier Spend Analytics – Fortune 500 Oil & Gas

• Developed Power BI dashboards to reveal procurement inefficiencies across supplier categories.
• Enabled more than $10M in cost savings by surfacing actionable opportunities in category spend and vendor performance.
• Led and mentored a sub-team of analysts, ensuring technical quality and on-time delivery across multiple analytics workstreams.

Feedstock Optimization & What-if Scenarios – Petrochemical

• Built a linear programming model in Python/OR-Tools to optimize feedstock allocation under capacity and curtailment constraints, achieving 30% uplift in profit margins.
• Automated yield and contribution margin computations, reducing reporting time from days to minutes.
• Designed star-schema data models on MS SQL Server for real-time monitoring and scenario analysis.

Real-time Asset Performance System – Fortune 500 Oil & Gas

• Architected end-to-end ETL pipelines and star-schema models using RapidMiner, Python and SQL for asset performance dashboards.
• Defined and implemented 15+ KPIs with stakeholders, replacing fragmented reports with a unified, live monitoring system.

Education

• B.C.A in Data Science (CGPA 9.4), B.S.A.R Crescent Institute of Science & Technology (2017–2020).

Academic partnership & collaborations

• Engaged in academic partnership programmes and collaborative interactions with Christ University, Bengaluru, gaining exposure to contemporary teaching approaches and course structures in analytics and data science.
• Leverages these academic insights to recommend best practices and enrichment ideas for Computer Science, AI and Data Science programmes.

Certifications

• SQL Essential Training & Programming Foundations: Databases – LinkedIn Learning.
• Machine Learning with Python (Level 1) – IBM & Cognitive Class.

Engagement with the Department

• Industrial Adjunct Faculty and Mentor for the Department of Data Science & AI, supporting B.Sc. Computer Science with Data Science and B.Sc. Computer Science with AI.
• Delivers guest lectures, masterclasses and practical labs on Python, SQL, ML, data modelling, big data tools (HiveQL, Spark, PySpark) and business analytics.
• Brings industry case studies from supply chain, oil & gas and retail/CPG into core and elective papers.

Student mentorship & project guidance

• Guides student projects on real-world problems – demand forecasting, procurement analytics, optimization, dashboard design and performance monitoring.
• Coaches students on problem framing, requirement gathering and stakeholder communication so that project outputs are both technically sound and business-relevant.
• Supports hackathons, mini-projects and capstone reviews with feedback on modelling choices, evaluation metrics and presentation style.

Curriculum & career value

• Provides feedback on curriculum to ensure strong alignment with current tools used in industry (Python, SQL, Spark, PySpark, Power BI, SnowflakeDB).
• Helps students map their skillsets to roles such as Data Analyst, Business Analyst, ML Engineer and Supply Chain Analyst.
• Emphasizes professional skills – stakeholder management, gap analysis, documentation and communication – that are critical for workplace readiness.

• SPOT Award – End-to-end ownership of Feedstock Optimization solution (Mu Sigma).
• SPOT Award – Mentoring and developing junior analysts (Mu Sigma).
• SPOT Award – Multi-role contribution to 2024 training programme (Mu Sigma).
• IMPACT Award – Conducting internal L&D trainings beyond core project responsibilities.
• PINNACLE Awards – Recognized multiple times at KIPI.AI for business discovery, stakeholder value-add and identifying new analytics opportunities.