Senior Applied Data Scientist, Trucking

Key Skills

Algorithms, Analytical and Problem solving, C++, Data science techniques, Design, Forecasting, Java Programming, Machine learning techniques, Natural Language Toolkit - NLTK, Optimization, Perl Programming, Python Programming, Ruby on Rails, Scikit-learn, SQL, Statistics, Supply Chain Management

Job Description

Build the programs to help Flexport grow

Flexport is building the first modern logistics platform to make global trade easier for everyone. We are solving complex problems on a global scale, and disrupting a multi-trillion-dollar industry that has remained stubbornly unchanged.

Trucking engineering

The trucking team’s mission is to make Trucking efficient, reliable, and transparent for our operators, carriers, and shippers. We simplify the shipping process by minimizing effort for carriers, shippers, and partners. We solve execution at the endpoints, in the carrier's hands, and in the tools used by shippers, not only in our 4 walls. We deeply care about the success of our carriers as a foundation for the success of our shippers. And to make this happen, we need exceptional planning/pricing tools to ensure that shipments are tendered to the optimal carrier, via the optimal mode, and on the optimal route through dynamic carrier allocation and tools that take into account carrier cost, carrier performance (OTE, tender acceptance, load failure rate), market information, congestion information, customer service requirements and modal options (Dray, Drayload, TL, LTL, etc).

The opportunity

Flexport is looking for a creative, technically-minded Senior Applied Research Scientist (ARS) who is motivated to solve some of the world’s most challenging problems in global trade.

Data is at the heart of our business, and as an Applied Research Scientist, you will develop first-in-class science products to make global trade easy and efficient. In collaboration with multidisciplinary product, engineering, and business/operations teams, you will apply advanced Operations Research (OR) and Machine Learning (ML) methods to deliver data-driven insights and automated decision-making solutions for our Truckload products.

Our business, product, and engineering teams collaborate closely with our ARSs to share domain knowledge, test hypotheses at scale, and develop promising solutions that can be quickly and widely deployed. We are passionate about providing effortlessly accessible intelligence and actionable insights to our end users. Our ideal candidate is: self-motivated, highly analytical, technically excellent at writing code, and passionate about delivering cutting-edge solutions.

You will:

• Lead research, development, and production deployment of large-scale planning optimization solutions. The end results will be first-in-class planning systems that support (near) continuous planning in various freight modes.
• Work collaboratively with product, engineering, and business to:
• find opportunities to improve and enhance our technology products, and
• translate ambiguous business requirements into the right OR/ML solution.
• Research prior work to inform and develop models and algorithms and quantify appropriate metrics & targets.
• Deliver compelling data-driven solutions to support automated decision-making at scale.
• Work with large and complex data sets. Solve difficult data analysis problems by applying advanced analytical methods as needed.
• Communicate findings to technical collaborators and business stakeholders.

You should have:

Minimum Qualifications

• Ph.D. (or equivalent industry or research experience) in quantitative fields, such as Operations Research, Computer Science, Mathematics, etc. 
• 5+ years of industry experience in solving transportation/logistics optimization problems and developing practically efficient solution strategies for large and extreme-scale networks.
• Experience and a strong background in algorithm design, engineering, and implementation.
• Experience and a strong background in optimization methods for solving linear, mixed-integer, and dynamic programs.
• Understanding of MIP strategies to customize/leverage commercial/open-source solvers.
• Experience in business analytics, forecasting, or supply chain planning, emphasizing quantitative modeling and analysis.
• Software development experience using general-purpose programming languages like Python, Java, C, C++, or C#.
• Experience working with large data sets and knowledge of tools for big data analytics (e.g., SQL, Python, Perl, or Ruby).
• A compliance first attitude to keep our regulators happy and enthusiastic about Flexport since we operate in a heavily regulated industry.

Preferred Qualifications

• Advanced knowledge of decomposition/iterative methods for solving large-scale optimization problems.
• Expertise in designing and implementing optimization models and algorithms for large-scale discrete/combinatorial problems (e.g., vehicle routing, inventory planning, scheduling, network design, scheduling, and facility location).
• Expertise in developing metaheuristics and metaheuristics algorithms for extreme-scale combinatorial optimization.
• Proven object-oriented design and implementation skills (e.g. Python, Java, or C++).
• Some experience in machine learning and statistical techniques such as classification, clustering, regression, statistical inference, collaborative filtering, and experimental design.
• Some experience in business analytics, forecasting, or supply chain planning, emphasizes quantitative modeling and analysis.
• Strong research track record with contributions to research communities via publications in top conferences and journals and code contributions in open-source communities such as COIN-OR, scikit-learn, CLTK, NLTK, etc.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.