A world class team is one in which all your colleagues are exceptional at what they do and are highly effective collaborators. The value and satisfaction of being on such a team is astounding. At Stord, we are laser focused on building a world class data science function.. and we are well on our way.

Our Data Scientist will join a high caliber team within our Data Science division and will be responsible for building statistical and ML models to help automate and/ or optimize our robust chain functions. The successful candidate will have a passion for solving challenging problems and will have a wealth of experience using SQL and Python to develop, maintain, and deploy enterprise grade statistical and ML models in production. 

What You’ll Do:

• Build, deploy, monitor, and maintain enterprise grade statistical and ML models and decisioning systems in production to help optimize/ automate business processes
• Continuously monitor deployed models and experiment with different algorithms/ novel approaches to improve productionized systems’ performance
• Partner closely with various internal customers (Freight, Fulfillment, Product, and Finance teams) to understand business requirements, providing feedback on feasibility, and implementing solutions that drive business performance
• Collaborate with the data engineering team to identify ways to improve the quality of the cloud-based data warehouse
• Create and maintain comprehensive technical documentation to educate both internal and external customers about our systems
• Manipulate and analyze complex, high-volume, high-dimensionality data from various sources using a variety of tools and data analysis techniques to identify gaps in the system and potential enhancements
• Communicate verbally and in writing to key business stakeholders with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations
• Acts as an advocate for continuous improvement, identifying opportunities and efficiencies to improve our existing systems and/ or MLOps process as a whole

What You'll Need:

• Master’s degree in a quantitative field such as Statistics, Applied Mathematics, Physics, Engineering, Computer Science, Operations Research or Economics
•  1.5 years of relevant industry experience in an analytical role involving big data extraction, analysis, statistical/ ML modeling, and delivering advanced analytics solutions 

• Deep technical and data science expertise

• Experience with core statistical analytical techniques, data mining, and predictive modeling is required (one or more of the following) : 

• • regression analyses (linear regression, logistic regression, quantiles, etc.)

• • machine learning (neural networks, XGBoost, Random Forest, SVM, deep learning, etc.)

• • segmentation/ clustering techniques (K-means, etc.)

• • network analysis (location-allocation, travelling salesperson, vehicle routing problem)

• • Simulation (Monte Carlo, dynamic, discrete event)

• • Optimization (linear and nonlinear programming, heuristic)

• • time series analysis (ARIMA, VAR, etc.)

• • Graph theory (Breadth-first search, Depth-first search)

• • Recommender systems (collaborative filtering, content-based filtering, etc.)

• • Geographic cluster recognition and manipulation techniques

• • text mining & unstructured data analytics

• Strong competency with big data analytics tools:

• • Languages (must have): Python, SQL

• • Libraries (must have expertise in at least one): TensorFlow, PyTorch, Scikit-learn, Keras, Numpy, Theano, Keras, Pandas, Matplotlib

• • Cloud Ecosystems (must have expertise in at least one): GCP, AWS, Azure

• • Data Warehouses (must have expertise in at least one): BigQuery, Redshift, Synapse

• • SQL Databases (highly desirable): MySQL, Postgresql, Microsoft SQL Server

• • NoSQL Databases (highly desirable): MongoDB, Cassandra, DynamoDB, Datastore

• • Analytics Platforms (nice to have): Databricks, Vertex AI, Dataiku, Alteryx, etc.

• • Data Visualization Tools (nice to have): Power BI, Sisense, Tableau, Lookr, Domo, etc.

• Familiarity with MLOPs: Git branching, CI/CD/CT

​Bonus Points:

• Preferably with a background in Supply Chain, Logistics, or Transportation