About Delta Tech Hub:
Delta Air Lines (NYSE: DAL) is the U.S. global airline leader in safety, innovation, reliability and customer experience. Powered by our employees around the world, Delta has for a decade led the airline industry in operational excellence while maintaining our reputation for award-winning customer service. With our mission of connecting the people and cultures of the globe, Delta strives to foster understanding across a diverse world and serve as a force for social good. Delta has fast emerged as a customer-oriented, innovation-led, technology-driven business. The Delta Technology Hub will contribute directly to these objectives. It will sustain our long-term aspirations of delivering niche, IP-intensive, high-value, and innovative solutions. It supports various teams and functions across Delta and is an integral part of our transformation agenda, working seamlessly with a global team to create memorable experiences for customers.
Why join?
- Technology is a key enabler of the differentiated services that Delta provides. At the DTH, you get the opportunity to work on projects with a significant impact on business outcomes and customer experience.
- Deepen your knowledge by taking part in multifaceted learning and development programs –exposure to extensive internal and partner repositories, institutional affiliations, and industry SIG (Special Interest Groups) partnerships.
- Collaborate with research, innovation and IP co-development partners.
- Immerse yourself in an employee-centric culture.
- Develop deep and broad business acumen on airline operations while retaining focus on cutting-edge technology driven solutions.
- Avail a full range of benefits that support you and your family: Insurance, Commute, Meals, and Special Travel opportunities.
- Design, build, and productionize AI solutions—especially LLM and generative AI workloads—on top of our Enterprise data Platform (Databricks, Azure, Open AI, and AWS). This role has an emphasis on and operationalization of AI solutions, ensuring AI products are reliable, scalable, secure, and cost effective in production. You will partner with data engineering, data science, and product teams to turn ideas into robust, continuously running services.
KEY RESPONSIBILITIES:
- Lead high-impact analytical and modelling projects from problem definition to measurable business outcome.
- Translate ambiguous commercial questions into well-structured statistical or optimization problems.
- Design and run robust analyses, including:
- Hypothesis testing
- Experimental design (A/B and quasi-experimental)
- Power calculations
- Model validation and back testing
- Build predictive and prescriptive models using appropriate statistical and machine-learning methods.
- Critically assess model assumptions, bias/variance trade-offs, overfitting risks, and data limitations.
- Clearly communicate uncertainty, limitations, and trade-offs to non-technical stakeholders.
- Partner with engineering teams to ensure models are implemented reliably and responsibly in production.
- Contribute to our standards for validation, documentation, and reproducible analytical practice.
WHAT YOU NEED TO SUCCEED (MINIMUM QUALIFICATIONS):
- 4–7+ years in software and Data Science experience
- Strong foundations in statistics and probability, including:
- Hypothesis testing and confidence intervals
- Regression modelling and diagnostics
- Experimental design and causal reasoning
- Understanding of sampling, bias, variance, and uncertainty
- Demonstrable experience applying statistical or ML models to real business problems.
- Ability to explain:
- Why a model works
- When it won’t works
- What assumptions it relies on
- How confident we should be in its outputs
- Strong Python skills (e.g. pandas, scikit-learn, PySpark or similar) and solid SQL capability.
- Experience validating models properly (cross-validation, holdouts, back testing, sensitivity analysis).
- Clear and confident communication with both technical and non-technical stakeholders.
- A degree (or equivalent experience) in statistics, mathematics, computer science, engineering, or a related quantitative field.
- We value candidates who can reason deeply about a problem — not just apply a library.
WHAT WILL GIVE YOU A COMPETITIVE EDGE (PREFERRED QUALIFICATIONS):
- Experience with optimization methods or operations research.
- Exposure to causal inference techniques (e.g. matching, uplift modelling, diff-in-diff).
- Experience applying NLP or GenAI in a statistically responsible way.
- Familiarity with model lifecycle tools (e.g. ML flow, Databricks)
Behavioral Competencies:
- Ability to produce high quality results, work in a collaborative environment by embracing diverse perspectives and with a solution-based approach.
- Adapt communication clearly and concisely based on team dynamics and expresses thoughts & ideas effectively.
- Ability to engage effectively with peers and stakeholders to build trust and reliable working relationships.
- Ability to understand business processes, implement innovative solutions, guide juniors on continuous improvement by constantly updating oneself on current technology & trends.
- Inquisitive to understand customer and business expectations while creating value addition on technical solutions.
