Research Scientist II, Last Mile Science

Research Scientist II, Last Mile Science

Are you passionate about solving complex logistics challenges? Our Analytics team is at the forefront of enhancing delivery experiences through data-driven solutions and innovative technology. As a Research Scientist, you will join a team dedicated to optimizing our delivery network, ensuring reliable and efficient service to our customers. We are seeking an enthusiastic, customer-centric professional with strong analytical capabilities to drive impactful projects, implement advanced solutions, and develop scalable processes.
In this role, you will have immediate ownership of business-critical challenges and the opportunity to make strategic, data-driven decisions that shape the future of our delivery operations. Your work will directly influence customer experience and operational excellence. The ideal candidate will possess both research science capabilities and program management skills, thriving in an environment that requires independent decision-making and comfort with ambiguity.
This role offers the opportunity to make a significant impact on our advanced logistics network while working with pioneering technology and data science applications.
Basic qualifications
• 3+ years of building machine learning models for business application experience
• Knowledge of programming languages such as C/C++, Python, Java or Perl
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred qualifications:
• PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
• 3+ years of extensive relevant research experience
• Deep expertise in Machine Learning
• Proficiency in programming
• Core competency in mathematics and statistics
• Track record of successful projects in algorithm design and product development
• Publications at peer-reviewed conferences or journals
• Strategic thinker with good execution skills
• Exhibits excellent business judgment
• Effective verbal and written communication skills
• Experience working with real-world data sets and building scalable models from big data
• Experience with modern modeling tools and frameworks such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow
• Experience with large scale distributed systems

Basic Qualifications

- PhD, or Master's degree
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience analyzing both experimental and observational data sets
- 3+ years of building machine learning models for business application experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

Preferred Qualifications

- Knowledge of R, MATLAB, Python or similar scripting language
- Experience with agile development
- Experience building web based dashboards using common frameworks
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- 3+ years of applied research experience
- Knowledge of deep learning, machine learning and statistics
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- Knowledge of mathematical/statistical/physics fundamentals
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Track record of successful projects in algorithm design and product development.
- prior experience with mentorship and/or management of scientists
- Thinks strategically, but stays on top of tactical execution.
- Exhibits excellent business judgment; balances business
- Effective verbal and written communication skills
- Experience working with real-world data sets and building scalable models from big data.
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow,
- Experience with large scale distributed systems

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