Lead Data Scientist

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Mohammad Arani

CA, USA 501-***-**** *****.********@*****.***

LinkedIn Google Scholar

PROFESSIONAL OBJECTIVE

Accomplished Data Scientist with over 8 years of experience in applying advanced machine learning techniques, statistical modeling, and data analytics to solve complex business challenges. Expertise in designing predictive and prescriptive models, mathematical modeling (operation research), implementing scalable data-driven solutions, and driving actionable insights across industries including logistics, supply chain, and financing. Proficient in Python, SQL, and big data platforms like Databricks and Spark, with a proven track record of building robust data pipelines and deploying production-ready solutions end-to-end. Adept at leading cross-functional collaborations, mentoring teams, and leveraging reporting/visualization tools such as Power BI, and PlotlyDash. Passionate about transforming data into intelligence to inform strategic decisions and foster innovation and help managers make informed decisions. Excited to contribute to innovative projects, creating impactful solutions that drive growth and operational excellence to corporations. PROFESSIONAL SUMMARY & KEY SKILLS

* Expertise in Machine Learning & Statistical Modeling; * Programming: Python (pandas, scikit-learn, PyTorch, TensorFlow), SQL; * End-to- End Model Development: Ideation to Productionalization; * Knowledge of ML Pipelines & Engineering Architecture; * Advanced Mathematical

& Statistical Analysis; * Operations Research (Linear & Non-linear Optimization, Mixed Integer Programming); * System Modeling & Simulation Optimization; * Proficiency in Google OR-Tools, CPLEX; * Data Wrangling & Preprocessing; * A/B Testing & Statistical Hypothesis Testing;

* Data Visualization: Plotly, Dash; * Effective Communication of Technical Results to Stakeholders; * Agile Development & CI/CD Pipelines;

* Cross-Functional Collaboration & Leadership.

SELECTED CERTIFICATES

Udemy© Online Courses Certificates: Master Time Series Analysis and Forecasting with Python 2025; Certified Risk Management FMEA ISO 31000 Expert Accredited; Data Science and Supply Chain Analytics. A-Z with Python; Machine Learning A-Z: Hands-On Python & R in Data Science; Deep Learning A-Z: Hands-On Artificial Neural Networks; The Complete SQL Bootcamp; Python for Time Series Data Analysis; Optimization with Python: Complete Pyomo Bootcamp A-Z; Complete Data Analyst Bootcamp from Basics to Advanced; Microsoft Power BI Desktop for Business Intelligence; etc.

EMPLOYMENT HISTORY

Lead Data Scientist 03/2025-Present

Crossroads Equipment Lease and Finance

Credit Risk Models: Developing Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) models. Tools: Python (Lifelines, Statsmodels, pandas, numpy), SQL Research Scientist II (Data Scientist and Operations Research Scientist) 08/2021-03/2025 DP World, Applied Science Team

Selected Projects in Commercial Intelligence, Sales and Marketing: Global Market Price Prediction for Ports: Developed time series and machine learning models to forecast market price trends across global ports, predicting minimum, maximum, and average prices over the next 30 days. Tools: Python (PySpark, Databricks, pandas, scikit-learn, statsmodels, SciPy), Keras, Prophet, SQL. Sales and Engineering Chatbot Development: Fine-tuned large language models to provide real-time, data-informed responses for SeaRates ERP Documentations, using Retrieval-Augmented Generation, text-to-SQL, table-to-text models for improved database interactions, and user documentations. Tools: Python (LLM, Hugging Face), NLP, SQL. Container Vessel Cost Model: Designed an extensive cost model for container vessel operations globally, supporting financial decision-making by estimating costs based on route, vessel specifications, and load. Integrated modules for port wait time, emissions, system behavior analysis, and visualization. Tools: Python (Plotly Dash, pandas, scikit-learn, SciPy, Shapely), SQL.

Global Shipping Network Simulation Optimization: Developed an optimization routing algorithm to minimize shipping costs and transit times by analyzing port fees and service routes. Used graph-based methods to identify optimal hub placements and conducted profitability simulations with over 160 million container events. Tools: Python (NetworkX, pandas, polars, discrete event simulation).

Port Charges Estimation: Estimated port fees based on vessel size and class using regression models to assist budgeting and cost analyses. Tools: Python (pandas, scikit-learn, SciPy), SQL. Lead Scoring Algorithm: Designed and implemented a predictive lead scoring model to rank and prioritize leads in SeaRates' CRM. The algorithm utilized customer request data, shipment details (e.g., number of containers, origin and destination ports), and customer history to assign scores for optimized sales targeting. Tools: Python, PySpark, Pandas.Data Visualization for Stakeholder Reporting: Built dashboards and visual reports for stakeholder insights using Power BI and Plotly Dash, with integrated Python and R libraries for advanced data presentation. Tools: Python, Power BI, DAX, SQL. Web Scraping and API Automation: Conducted data extraction and scheduling tasks for automated insights from online sources and APIs using Python scripts, integrated workflows, and Databricks scheduling. Tools: Python (requests, BeautifulSoup, Selenium, SQLAlchemy), SQL, Windows batch scheduling. Selected Projects in Port & Terminal Operations:

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Vessel ETA for US Ports: Enhanced vessel ETA accuracy through big data processing and GIS analysis of AIS data, boosting terminal efficiency with predictive machine learning models. Tools: Python (commercial GIS data), data visualization, machine learning.

Appointment Time Optimization for Port of Antwerp: Created a recommendation system for appointment times based on truck companies' historical scheduling preferences and port operational constraints, enhancing logistics efficiency. Tools: Python (pandas, numpy, scikit-learn, sktime, tsfresh), SQL. Yard Optimization for Port of Pusan: Developed a two-stage mathematical model to assign discharged containers to blocks and optimize crane moves for efficient storage and retrieval, reducing operational delays. Tools: Mixed Integer Linear Programming (Python, Google OR-Tools, CPLEX).

Inventory Optimization for Yard Management: Built predictive models for container dwell time and exit mode and developed a mathematical model to minimize shuffling during retrieval, enhancing yard efficiency. Tools: Machine Learning, Mixed Integer Linear Programming (Python- Keras, Google OR-Tools, CPLEX). Container Shuffling Optimization: Created algorithms to replay container movements and optimize retrieval of buried containers, providing real-time metrics to stakeholders for decision-making. Tools: Python, SQL, Power BI. Graduate Teaching Assistant, Lecturer, and Research Assistant 08/2017-05/2021 The University of Arkansas at Little Rock, Little Rock, Arkansas Courses: Machine Learning & Deep Learning, Discrete Event Systems Modeling and Simulation with Arena, Advanced Operations Research I, and II, Linear and Non-Linear Optimization Techniques, Heuristics and Meta-Heuristics Algorithms, Decision and Risk Analysis, Advanced Engineering Economy, Introductory and Advanced Statistics, Supply Chain Management, Transportation and Logistics Management, Inventory Control and Management, Quality Control and Management.

Laboratories: (A) Laboratory of Intelligent Transportation Systems, led by Prof. Yupo Chan (08/2017-12/2019), (B) Laboratory of Network Optimization and Operating Systems, led by Prof. Xian Liu (01/2020-05/2021). Dissertation: Blood supply chain network design, A) optimizing blood inventories at hospitals and blood banks considering blood shelf lives, B) optimizing mobile blood collection vehicle routing, C) optimizing location allocation of blood facilities, D) simulation optimization of the entire network (Deterministic and stochastic mathematical modeling, CPLEX mathematical programming and constraint programming, discrete event simulation via ARENA, python) Operations Research & Data Analyst 01/2017-08/2017 Bronze Industrial Group

Responsibilities: Analyzing End-product Costs, Providing Weekly Production Plan for a Production Line, Development of Computer Simulations and Computer Modeling for Complex Processes and Operations Including Parallel Machine Scheduling, Creating Enhanced Data Visualization and Dashboard Representation for Managerial Decision Support and Analysis System, Preparing Technical Production Reports and Project Reports. Main Project: developed unrelated parallel machine scheduling mathematical model to produce weekly production plan, optimizing inventory, satisfying demand and their due dates, production recourse constraints. (C++, CPLEX toolbox, SQL)

Project Controller 02/2014-02/2015

Marand Glass Fiber Development Company

Responsibilities: Employing Computer Modeling for Feasibility Study by COMFAR III, Conducting Bidding and Assessing Bidders’ Technical Engineering Documents, Pursue Technology and Skill Transfers, Preparing Technical Project Reports, Technical Data Generated and Documentations. SKILLSET

Programming Languages and Tools: Python (extensive libraries, OOP), SQL, C++, MATLAB; Data Visualization & Reporting: Power BI, Plotly Dash, ggplot2; Machine Learning Frameworks: PyTorch, TensorFlow; Optimization & Simulation Tools: Arena, GAMS, LINGO, LINDO, CPLEX, Google OR-Tools; Data Analytics & Experimentation: Statistical hypothesis testing, A/B testing, impact analysis; Data Engineering & Analytics: PySpark, pandas, NumPy, SPSS, Minitab; Productivity Tools: MS Office Suite. EDUCATION

University of Arkansas at Little Rock 08/2017-05/2021 Ph.D. in Engineering Science / Systems Engineering (ENSC/SYEN) Dissertation: Design and Sensitivity Analysis of Blood Supply Chain Network, The Merits of Lateral Resupply. Azad University of Qazvin – Science and Research, (AUQ) 08/2011-05/2013 Master of Science in Industrial Engineering

Thesis: Multimode Preemptive Resource Investment Problem Subject to Due Dates for Activities: Formulation & Solution Procedure Azad University of Karaj (AUK) 08/2007-05/2011

Bachelor of Science in Industrial Engineering

WORK AUTHORIZATION

US permanent resident (green card holder) since February 2023.

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