Machine Learning Scientist
Build the programs to help Flexport grow.
Flexport is looking for a creative, technically-minded Machine Learning Scientist (MLS) who is motivated to solve some of the world’s most challenging ML problems in global trade.
Data is at the heart of our business, and as a Machine Learning Scientist, you will work to evaluate and provide insights into our physical and digital products. In collaboration with multidisciplinary product, engineering, user experience, and business/operations teams, you will apply advanced Machine Learning (ML) methods to deliver data-driven insights and automated decision solutions in Flexport’s freight forwarding products.
Our business, product, and engineering teams collaborate closely with our Machine Learning Scientists to share domain knowledge, test hypotheses at scale, and develop promising solutions that can be quickly and widely deployed. In addition, we are passionate about providing effortlessly accessible intelligence and actionable insights to our end users. Thus, the ideal MLS candidate is: self-motivated, highly analytical, technically excellent at writing code, and passionate about delivering cutting-edge solutions.
- Work collaboratively with product, engineering, and business to:
- Find opportunities to improve and enhance our forecasting technology products.
- Understand Flexport’s business and operations processes to identify impact opportunities.
- Translate ambiguous business requirements into the right technical solution.
- Design and build robust and scalable production forecasting solutions.
- Perform R&D of new ML models and refactor ML solutions to support scalable production deployment.
- Explore and work with large and complex data sets to implement robust feature and signal extraction models to identify signals that support better decision-making.
- Deliver compelling data-driven estimation solutions to support automated decision-making at scale.
- Research prior work to inform and develop rational hypotheses and quantify appropriate metrics & targets.
- Work collaboratively with other scientists (e.g., operations research, optimization) to develop hybrid solutions that combine machine learning and optimization to automate decision-making.
- Develop prototype data analysis/machine learning pipelines iteratively as needed to generate actionable insights.
- Communicate findings to technical collaborators and business stakeholders.
- Perform requirements gathering and data analysis.
You Should Have:
- Masters degree in quantitative fields (e.g., computer science, mathematics, statistics, physics, engineering, etc.)
- Experience and strong technical background in one or more of the following: Machine Learning, Natural Language Understanding, Computer Vision, Data Mining, Artificial Intelligence, Numerical Optimization, Data Engineering.
- 3+ years of industry experience building, iterating, validating, and deploying statistical and/or machine learning models.
- Software development experience using general-purpose programming languages like Python, Java, or C/++, C#
- Experience working with large data sets.
- Strong verbal and written communication.
- Experience training Machine Learning models on libraries such as Tensorflow, PyTorch, Scikit-learn.
- Ph.D. in quantitative fields (e.g., computer science, mathematics, statistics, physics, engineering, etc.)
- A strong theoretical background in machine learning/artificial intelligence, algorithms, distributed systems, or statistics.
- Experience training machine learning models in a cloud computing environment like Amazon EC2, Google Cloud Platform, Microsoft Azure, etc.
- Experience in machine learning and statistical techniques such as classification, clustering, regression, statistical inference, collaborative filtering, and experimental design.
- Experience taking research prototypes to production.
- Some knowledge of the transportation and logistics industry.
- Proven object-oriented design and implementation skills (Python, Java, and C++),
- 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 scikit-learn, CLTK, NLTK, etc.
At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make it easy and accessible for everyone. We’re shaping the future of a $8.6T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year.
The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. At a valuation of $8 billion, we’re experiencing record growth and are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us.
Worried about not having any logistics experience?
Don’t be! Our mission is to make global trade easy for everyone. That’s why it’s important to bring people from diverse backgrounds and experiences together with our industry veterans to help move the global logistics industry forward.
We know this industry is complex. That’s why we invest in education starting day one with Flexport Academy, a one week intensive onboarding program designed specifically to set every new Flexport employee up for success.
At Flexport, our ability to fulfill our mission of making global trade easy for everyone relies on having a diverse, dedicated and engaged workforce. That is why Flexport is committed to creating and nurturing an environment where anyone can be their authentic self. All qualified applicants will receive consideration for employment regardless of race, color, religion, sex, national origin, age, physical and mental disability, health status, marital and family status, sexual orientation, gender identity and expression, military and veteran status, and any other characteristic protected by applicable law.
Tags: Azure Classification Computer Vision Data analysis Data Mining Distributed Systems EC2 Engineering Google Cloud Machine Learning ML ML models NLTK Open Source Python PyTorch R R&D Research Scikit-Learn Statistics TensorFlow
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