Staff Data Scientist

Atlas Air•Miami, FL

11d•$165,000 - $225,000

About The Position

We are looking for a brilliant and highly motivated Staff Data Scientist to join our innovative Data Analytics and Optimization team! This isn't just another analytics role – you'll be at the forefront of transforming Atlas Air through the power of data. In this position, you will develop data-driven technology solutions for a variety of high-dimensional resource management problems in aviation involving complex trade-offs under uncertainty. You will collaborate with leaders across our organization to uncover hidden opportunities, tackle challenging data puzzles, and build sophisticated predictive and prescriptive models that drive real-world impact. Your insights won't just live in dashboards – the fruits of your work will shape our strategic direction, be operationalized in our processes, and will fuel our competitive advantage. The perfect candidate brings a powerful blend of programming prowess, machine learning mastery, and operations research skillfulness, along with the rare ability to translate complex technical concepts into compelling stories that inspire action among non-technical leaders. If you're passionate about using cutting-edge science and technology to solve meaningful problems and want to be part of a team that values your analytical superpowers, this role is your next adventure!

Requirements

Master’s degree or Ph.D. in Operations Research, Machine Learning, Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
5+ years of hands-on experience in a data science or similar analytical role, with a track record of impact.
Expertise in programming languages such as Python, R, or similar programming languages for data analysis.
Proficiency with data manipulation tools (e.g., SQL, Pandas, Spark) and machine learning libraries (e.g., scikit-learn, PyTorch, TensorFlow, etc.).
Strong knowledge of statistical analysis and hypothesis testing.
Strong understanding of statistical modeling, machine learning algorithms, hypothesis testing, and optimization.
Excellent communication, presentation, and interpersonal skills with the ability to translate complex technical concepts to non-technical audiences.
Proven ability to translate business requirements into technical solutions.
Proven ability to apply software engineering best practices.
Experience working in production-grade Python code including proficiency with git, testing, and other software engineering best practices.

Nice To Haves

Master’s degree or Ph.D. in Operations Research, Machine Learning, Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
Domain expertise in aviation, transportation, or logistics.
History of technical leadership on significant data science initiatives.
Contributions to related research publications and/or open-source projects.
Experience with big data platforms (e.g., Spark/Databricks).
Experience with cloud platforms (AWS, GCP, or Azure) and MLOps practices.
Experience with optimization libraries (OR-Tools, Gurobi, or CPLEX)

Responsibilities

Collaborate with cross-functional teams including engineering, product, and business stakeholders to identify opportunities for leveraging data to drive business solutions around airline operations.
Lead complex data science projects from conception to implementation, working with various stakeholders (e.g., global control center, pilots, sales, etc.) to define objectives, timelines and success metrics.
Translate business requirements into data science or analytics projects with well-defined deliverables and timelines.
Design and conduct experiments to test hypotheses and measure the impact of work against objectives.
Collect, process, clean, and analyze structured and unstructured data from various internal and external sources.
Extract, transform, and analyze large datasets from various sources.
Perform exploratory data analysis to uncover patterns, trends, and relationships within large datasets.
Design, develop, and maintain sophisticated decision support tools leveraging machine learning and optimization models and algorithms to solve business challenges and unlock value.
Create clear data visualizations and compelling narratives to communicate findings to technical and non-technical audiences.
Mentor less experienced data scientists, providing technical guidance, setting clear objectives, and fostering professional growth.
Stay current with emerging techniques and technologies in data science and machine learning.
Collaborate with data engineering to implement production-ready solutions.
Monitor model performance and iterate on solutions as needed.
Establish best practices and methodologies for the data science function.
Research and implement new methodologies and technologies to improve Atlas Air’s data and AI/ML