ATPCO is the foundation of flight shopping, providing pricing and retailing data, tools, and services to 500+ airlines, global distribution systems, sales channels, and technology companies. In addition, ATPCO links the entire airline community together, collaborating to develop industry standards for airline distribution and end-to-end technology solutions. As a result, ATPCO solutions work seamlessly across existing, new, and evolving technologies and methods from shopping to settlement. Airline-owned and reliably supporting air travel for more than 55 years, ATPCO is everywhere people buy flights.
We consider qualified applicants for employment without regard to race, gender, age, color, religion, national origin, citizenship status, marital status, disability, sexual orientation, protected military/veteran status, gender identity or expression, genetic information, marital status, medical condition, or any other legally protected factor.
ATPCO is seeking an experienced Senior Data Scientist to join our team dedicated to tackling some of the most exciting and impactful data challenges within the airline industry. This role offers an opportunity to develop innovative Artificial Intelligence (AI), Machine Learning (ML), and Data Science solutions for rapidly evolving airline industry, harnessing hundreds of terabytes of data daily, and leveraging the latest AWS technologies to drive innovation at scale.
As a Senior Data Scientist at ATPCO, you will play a critical role in shaping the future of airline pricing and demand analytics, transforming vast datasets into actionable. You will work closely with cross-functional teams, contributing to product innovations and enhancing the airline industry's data ecosystem. This role is ideal for those passionate about solving complex challenges and advancing the use of data to optimize airline operations and pricing strategies.
Key Responsibilities
Advanced Data Strategy & Pipelines:
Lead the gathering, cleaning, and preprocessing of complex time-series and other datasets from multiple sources (e.g., S3, Redshift, MySQL, APIs).
Design and optimize robust data pipelines that ensure high data quality and consistency for advanced modeling work.
Innovative Algorithm & Model Development:
Design, develop, and fine-tune advanced predictive models to forecast demand and changes in market trends, leveraging techniques such as deep learning, reinforcement learning, and statistical methods.
Create sophisticated algorithms to detect nuanced market dynamics—such as pricing undercuts, competitive position shifts, and demand anomalies—in close collaboration with subject matter experts.
Continuously evaluate model performance and iterate on solutions to enhance accuracy, reliability, and scalability, taking responsibility for the end-to-end lifecycle of AI models.
Machine Learning Optimization & Production Deployment:
Champion the integration of machine learning techniques to streamline data collection and improve delivery processes.
Oversee the deployment of models into production systems, ensuring seamless integration with real-time decision-making infrastructure.
Collaborate with data engineers and DevOps teams to guarantee that models operate under optimal conditions and can quickly adapt to changing data patterns.
Strategic Cross-Functional Collaboration:
Act as a key liaison between technical teams and business stakeholders, ensuring data-driven insights align with strategic business goals.
Mentor and guide junior team members while fostering a collaborative environment to support cross-functional project initiatives.
Translate complex analytical findings into actionable strategies, leveraging clear data visualizations, comprehensive reports, and engaging presentations.
Leadership & Continuous Improvement:
Provide technical leadership in the evaluation of advanced models, establishing best practices for model development, validation, and continuous improvement.
Proactively monitor emerging trends in data science and AI, integrating innovative practices into team workflows to maintain a competitive edge.
The Ideal Candidate
Proven Senior-Level Expertise:
Extensive experience as a Data Scientist with a demonstrated track record in developing and deploying advanced predictive models, particularly with time-series and structured/unstructured data.
Prior experience in leadership, mentoring, and guiding technical teams in a dynamic, results-driven environment.
Advanced Technical Proficiency:
Mastery of SQL and advanced programming skills in Python or R, with deep familiarity in data manipulation libraries (e.g., Pandas, NumPy, SciPy) and machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
In-depth understanding of statistical methods, machine learning algorithms, and state-of-the-art time-series analysis techniques.
Expertise in Cloud & Big Data Technologies:
Experience with cloud platforms and big data technologies (e.g., Apache Spark, AWS Redshift, AWS SageMaker) to support scalable model deployment and data processing.
Strategic Communication & Visualization:
Exceptional ability to articulate complex technical concepts to a diverse audience, including non-technical stakeholders, using data visualization tools (e.g., Tableau, AWS Quick Sight, Matplotlib, Seaborn) effectively.
Domain-Specific Experience:
Familiarity with the airline industry’s pricing, revenue management, distribution or network planning challenges is highly advantageous.
Educational Background:
Advanced degree (Master’s or PhD) in Computer Science, Statistics, Mathematics, Analytics, Airline Management or a related field, with a strong emphasis on AI and machine learning.
Salary Range : $117,700 – $155,700
*The disclosed range estimate has not been adjusted for applicable geographic differential associated with the location*
At ATPCO, we are deeply committed to diversity, equity, and inclusion. Our supportive policies promote work-life balance through flexible work arrangements, and we cultivate a workplace where every employee feels valued, respected, and a true sense of belonging.
All your information will be kept confidential according to EEO guidelines.
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