Anas Alanqar
Data Science | M.S. Business Analytics @ UCLA Anderson | Machine Learning | Optimization | Time-Series Analysis | Forecasting | Causal Inference | Gurobi | CPLEX
- Role
- Data Scientist - Supply Chain Optimization at Niagara Bottling
- Location
- Los Angeles, CA, US
- LinkedIn followers
- 500 followers
About Anas Alanqar
I\'m a Data scientist with 7 years industry work experience in developing and deploying predictive models and optimization algorithms. I\'m experienced with the entire data analysis workflow including data wrangling, data visualization, exploratory analysis, feature engineering, and machine learning. Currently pursuing an M.S. in Business Analytics and Data Science. PhD in Engineering Optimization and Data-Driven Modeling at UCLA.I create value from data. Specifically, I create predictive models and data analytics insights that drive business decisions. Data science interests me as it is the driving factor for new technology solutions. I also enjoy data storytelling and presenting to large technical and non-technical audiences including stakeholders and customers. MSBA @ UCLA appeals to me since it is an incredibly unique program that prepares strong technical data scientists who also have critical business analysis and decision-making mindsetLanguages: Python (SciPy, NumPy, Pandas, Matplotlib, Scikit-Learn, TensorFlow & Keras), SQL, R, MATLAB, C++Software: GitHub, Tableau, Power BI, GAMS Optimization, GAMS, IBM CPLEX, IBM ILOG CPLEX, Supply Chain Management, Gurobi, Gurobipy, Pyomo, AMPL, Mosel, PuLP, CVX, CVXPY, CVXOPT, IPOPT, FICO Xpress, FICO XPRESS-MP, FICO Xpress Mosel, Spark, AWS, MongoDB, DuckDB, Snowflake, Neo4jAnalytics: Machine Learning, Classification and Regression, Deep Learning and Neural Networks, Time Series Analysis & Predictive Models Development, A/B Testing, Statistical Inference, Causal Inference (Prescriptive Models)
Experience
Data Scientist - Supply Chain Optimization
Jun 2025 — Present · Los Angeles, CA, US
Supply Chain Optimization: Designed a capacity and pricing planning tool using Gurobi with mixed integer optimization to optimize transportation cost and inventory management Transportation & Logistics: Improved logistics network efficiency with data-driven modeling and optimization, enhancing delivery planning and reducing costs Strategic Decision Support: Analyzed complex data sets to uncover insights and validate optimization strategies, driving informed decision-making and communicating results effectively to stakeholders Gurobi and CPLEX ( IBM CPLEX, IBM ILOG CPLEX ), Supply Chain Management, Supply Chain Optimization, Linear Programming - Linear Optimization -(LP), Integer programming - Integer Optimization -(IP), Mixed Integer Linear Programming - Mixed Integer Linear Optimization -(MILP) Gurobi, CPLEX, Integer Programming, Linear Programming, Optimization, Nonlinear Optimization, Convex Optimization, Non-convex Optimization, Data Science, Supply Chain Management, logistics, Transportation, SciPy, Pulp, Pyomo, CVX, CVXPY, CVXOPT, IPOPT, GAMS, Mosel, AMPL, FICO Xpress, FICO XPRESS-MP, FICO XPRESS Mosel
Education
UCLA Anderson School of Management
Master of Science - MS, Business Analytics
UCLA
Master's degree, Predictive Modeling and Optimization Algorithms, Chemical Engineering
2013 — 2015
The University of Kansas
Bachelor of Science - BS, Chemical Engineering - Graduated with Distinction
UCLA
Doctor of Philosophy (PhD), Predictive Modeling and Optimization Algorithms, Chemical Engineering
2015 — 2017
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