Data Science Spring Co-op

Who we are:

Optimal Dynamics is on a mission to automate and optimize the logistics industry through the use of advanced analytics. We are based on more than three decades of R&D at Princeton University and represent the most sophisticated technology ever developed for the logistics industry. Optimal Dynamics is a high-growth early-stage company with ~70 employees (but changing very quickly!) and $56M in funding. 

About the team:

We are a team of bright, kind, and solution-oriented people focused on creating value for our customers. We can solve problems individually, but understand that the best solutions are found when the team brainstorms ideas together. We are excited about balancing the need to deploy new solutions quickly and designing solutions that are secured, reliable, maintainable and scalable for the long run.

Who you are:

• You are a quick learner and excited about learning new technologies.
• You thrive in an environment with lots of context and minimal guidance.
• You are detail oriented and adept at drawing real-world conclusions from data sets.
• You are adept at communicating and collaborating effectively with others.
• You are comfortable talking to stakeholders and understanding their business needs.

Responsibilities:

• Aid in the successful execution of model calibration for live customers.
• Work with customer-facing AI engineers to clean, identify patterns, and assess the quality of customer data.
• Improve analysis processes to create robust and reliable results.
• Communicate data findings to non-technical audiences in a professional manner.
• Work with the AI team to design scalable tests to automate the data discovery and cleaning process. Create robust methods to detect and possibly correct missing or poor data.

Qualifications:

• Available January-May 2023
• Actively enrolled in an undergraduate degree-seeking program in Mathematics, Computer Science, Industrial Engineering, Operations Research, Data Science, or related degree
• The ideal candidate will be expected to graduate between December 2023 through May 2024
• Experience with Unix command line navigation and shell scripting
• Experience quickly manipulating data in Microsoft Excel or Python, and interpreting the real world implications
• Interest in operations research and/or machine learning
• Ability to prioritize work and manage multiple projects and demands simultaneously

Nice to have:

• Familiarity with Docker and containerization
• Working knowledge of Java for debugging model errors and understanding stacktraces
• Experience with relational databases and SQL
• Understanding of file structures (XML, EDI, flat file, etc.)
• Experience with Cloud Computing platforms: Amazon AWS, Microsoft Azure, Google App Engine or similar
• Background knowledge in machine learning

Where:

• Hybrid - Remote with in-person work based in NYC or Atlanta

PLEASE NOTE THERE ARE NO BENEFITS OFFERED FOR THIS CO-OP.

Benefits:

• Equity
• Health / Dental / Vision 100% covered for employee and 50% for dependents
• Life Insurance
• Flexible Spending Account (FSA)
• 401(k) match
• Unlimited PTO (vacation, personal days, sick days, jury duty, military leave, bereavement) 
• 11 Holidays
• Paid Parental Leave for all employees
• Fitness Membership reimbursement
• Commuter benefits
• Flexible work from home policy

Optimal Dynamics is proud to be an equal opportunity employer that celebrates diversity and is committed to creating an inclusive workplace with equal opportunity for all applicants and employees. Our goal is to recruit the most talented people from a diverse candidate pool regardless of race, color, ancestry, national origin, religion, disability, sex (including pregnancy), age, gender, gender identity, sexual orientation, marital status, veteran status, or any other characteristic protected by law.

Optimal Dynamics is committed to working with and providing access and reasonable accommodation to applicants. If you require an accommodation, please reach out to careers@optimaldynamics.com once you've begun the interview process. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law.