Operations Research Scientist

Job Title : Data Scientist - Inventory Optimization and Operations Research

Location : Remote, EST East Coast Candidates

Contract : 06+ month contract Needs someone with DEEP experience on the Operations Research side building optimization models with CPLEX / Gurobi etc Job Summary :

We are seeking a highly skilled and experienced Data Scientist with a strong background in inventory optimization, operational research, and industrial engineering.

The ideal candidate will possess a deep understanding of inventory management principles, supply chain dynamics, and statistical modeling techniques.

Additionally, knowledge of optimal data structure design, data engineering, natural language processing (NLP) methods are plus.

In this role, you will be responsible for leveraging data-driven approaches to optimize inventory levels, streamline operational processes, and improve decision-making within our organization.

Responsibilities : Inventory Optimization : Apply advanced analytical techniques to optimize inventory levels, including demand forecasting, safety stock calculations, reorder point determination, and order quantity optimization.

Develop models to identify potential stockouts, excess inventory, and areas for improvement. Operational Research : Apply operational research methodologies to solve complex problems related to supply chain optimization, production planning, scheduling, and logistics.

Develop optimization models and algorithms to improve operational efficiency and reduce costs. Industrial Engineering : Analyze and improve existing processes, workflows, and systems to enhance productivity and reduce waste.

Apply industrial engineering concepts to streamline operations, eliminate bottlenecks, and improve overall efficiency. Statistical Modeling : Utilize statistical techniques and machine learning algorithms to analyze large datasets and extract meaningful insights.

Develop predictive models to forecast demand, identify trends, and support decision-making related to inventory management and operational planning.

Data Engineering and Database Design : Design and implement data pipelines, data structures, and database systems to efficiently collect, store, and process large volumes of data.

Ensure data quality and integrity throughout the data lifecycle. NLP and Generative Models : Leverage natural language processing techniques and generative models to analyze unstructured data, extract information, and develop text-based models for inventory optimization, demand forecasting, and decision-making.

Collaboration and Communication : Collaborate with cross-functional teams, including supply chain, logistics, operations, and IT, to understand business requirements, gather relevant data, and deliver actionable insights.

Present findings and recommendations to stakeholders in a clear and concise manner. Database Design and Optimization : Designed and developed the database schema and entity relations, ensuring efficient and normalized tables for optimal database performance.

Employed best practices in database design to enhance data storage, retrieval, and query performance. ETL Processes and Data Lake Design : Developed Extract, Transform, Load (ETL) processes to ingest and transform data from various sources into the data lake.

Designed the data lake zone and curated zone, establishing an organized and scalable data infrastructure that facilitated efficient data processing and analysis.

Qualifications : Ph.D. degree in Operations Research, Applied Math, Engineering Optimization or a related field.

Strong expertise in inventory optimization, operational research, and industrial engineering concepts and methodologies.

Proficiency in statistical modeling, machine learning, and optimization algorithms.

Experience with database design, data engineering, and data manipulation languages (e.g., SQL).

Knowledge of programming languages such as Python or R for data analysis and model development.

Familiarity with NLP techniques, text mining, and generative models.

Excellent problem-solving skills and ability to translate business requirements into analytical solutions.

Strong communication and presentation skills, with the ability to convey complex concepts to non-technical stakeholders.