Associate Data Scientist

Job Description

Kambr by Amadeus is a cutting-edge technology company revolutionizing airline revenue management tools. We are seeking an Associate Data Scientist to join our dynamic team. As an Associate Data Scientist at Kambr, you will play a pivotal role in leveraging data to develop industry leading analytic solutions for revenue management/dynamic pricing tools. Our ideal candidate for this role is someone who has strong analytical/communication skills, deep intellectual curiosity, and passion for travel and the aviation industry.

You will contribute to the development of machine learning and data products including business value definition, POC creation, functional data/process analysis and ultimately transitioning the concepts to a scalable production solution for our customer. This includes machine learning model building in Python using scikit-learn/Tensorflow and leveraging software engineering experience to develop and deploy scalable data engineering and model inference pipelines. You will develop, improve, and maintain team-wide architectural standards for development of data acquisition/transformation/modelling pipelines and machine learning services. In addition to this you will work closely with colleagues to identify and solve technology and process inefficiencies within the scope of tooling, CI/CD, and operational monitoring. This role will require both technical skill as well as coordination with business/domain subject matter experts. Clear presentation and articulation of concepts to both a technical and non-technical audience is required.

Common accountabilities:

• Has the required technical/functional knowledge and experience in own discipline. Knowledge of the Amadeus business and how it is related to own area.

• Works using existing procedures or guidelines and provides inputs to support/influence area decisions. Makes recommendations on new solutions and proposes improvements by analyzing different sources of information.

• Works with a moderate level of guidance and direction from manager.

Specific accountabilities:

• Implement data analysis algorithms on a large scale working closely with software engineering members.

• Create business solutions through a combination of science and software considering hypothesis by concrete business effect.

• Develop products / service cooperating with project manager, developer and business staff.

• Build & maintain the “Big Data” infrastructure.

• Track business effect through products and leading next action.

• Operate and manage product to keep product availability cooperating with operation staff

Required:

Undergraduate degree with quantitative focus, such as engineering, economics, mathematics, statistics, or similar.

Relevant work experience:

2-4 years of experience in an analytical role. Strong preference for commercial airline experience, especially airline revenue management

Technical Skills:

The ideal candidate possesses a foundation of software engineering skills (programming, testing, design, documentation, and collaboration) as well as real-world experience training and deploying machine learning models.

In addition to your technical skills, we are looking for a team-oriented individual who is passionate about building and maintaining a positive team culture. You should be a strong communicator and collaborator who is able to work effectively with cross-functional teams.

Skills

Computing

• SQL - Required.

• Python - Preferred.

• Looker/Tableau/Google Cloud/BigQuery/Airflow/Version Control - Nice to Have

Languages

• English

Specific knowledge

• Preferred - Experience with Airline Revenue Management or Network Planning

Diversity & Inclusion

Amadeus is an Equal Employment Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, or a related medical condition), ancestry, national origin, age, genetic information, military or veterans status, sexual orientation, gender expression, perception, or identity, marital status, mental or physical disability status, or any other protected federal, state, or local status unrelated to performance of work involved.