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Experienced Full Stack Data Analyst – Ancillary Revenue Data Scientist at arenaflex

Remote · USA Full-time New today

Join arenaflex's dynamic team as an Experienced Full Stack Data Analyst – Ancillary Revenue Data Scientist and contribute to driving business growth through data-driven insights.

About arenaflex

arenaflex is a leading airline company that operates with a strong commitment to innovation, customer satisfaction, and employee development. With a focus on delivering exceptional travel experiences, arenaflex has established itself as a trusted brand in the aviation industry. As a data-driven organization, arenaflex recognizes the importance of leveraging data analytics to drive business growth, improve operational efficiency, and enhance customer engagement.

Role Snapshot

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Start Date:

Immediate openings available

Position:

Experienced Full Stack Data Analyst – Ancillary Revenue Data Scientist

Compensation:

A competitive salary

Location:

Remote

Company:

arenaflex

Job Description

About the Role

As an Experienced Full Stack Data Analyst – Ancillary Revenue Data Scientist at arenaflex, you will play a critical role in driving business growth through data-driven insights. You will be responsible for creating and applying data visualization and machine learning techniques to progress ancillary revenue execution. As a key member of the Revenue Management team, you will collaborate with internal partners and external stakeholders to achieve rapid growth in customer-driven, tailored offers and business processes.

Key Responsibilities

* Design, execute, and deliver advanced quantitative analyses and multi-feature models to drive navigation and actions, either by experts or by systems; * Influence large data, capabilities in cloud environments, and multiple sources of data to identify signals and integrate those signals into modeling for explanation, prediction, or creation; *

Lead in satisfying other general analysis requirements;

* Perform Exploratory Data Analysis (EDA) to gain insights into customers' shopping behaviors, their response to arenaflex's offers, and how to better address their needs; * Create modeling theories involving multivariate statistical methodologies as well as current AI-based expressive methodologies; * Lead the execution and industrialization of the created models in the production system, including all stages of the code lifecycle; * Explain the results of quantitative analysis and multi-feature models and conveys to stakeholders, including senior management; *

Work primarily in Python, MS SQL, and other large data environments

* Provide expertise in coding and applied finance across Valuation, Revenue Management, and Ancillary groups; * Create and deliver customer-driven analysis, using cluster analysis, collaborative filtering, and randomized control testing; * Develop and maintain code standards, code library, and work processes where industrialized processes are essential; *

Participate in peer reviews of scientific plans and code to promote revenue growth;

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Assist, mentor, and guide junior colleagues;

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Aid the transition to streaming data for multiple sources

Essential Qualifications

* Four-year college education or higher in Finance, Computer Science, Statistics, Math, or related field required; * Graduate degree in Computer Science, Information Science, Business Analysis, or other systematically centered programs liked *

Past use of MS SQL, Python, and other large data technologies

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Past professional use of statistical analysis software liked

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Two (2) years of professional data analysis liked

* Experience in a carrier pricing, yield-or revenue management, revenue analysis, revenue systems, or similar role liked

Skills and Competencies

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Demonstrated ability to perform quantitative analysis and model development independently

* Ability to apply concepts from finance and revenue management to coding models and scientific items * Ability to summarize scientific methodologies and items and present insights and actions to upper management proficiently *

Excellent analytical and quantitative skills

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Excellent written and verbal communication skills

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Ability to pay attention to detail for reporting and analysis

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Ability to work collaboratively with different departments, partners, and staff

Work Environment and Company Culture

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Workplace:

A typical office environment, sufficiently heated and cooled

Physical Exertion:

Primarily not required

Supervision Received:

The occupant usually receives little guidance on daily work and receives general guidelines on new tasks

Positions Managed:

None

Career Growth Opportunities and Learning Benefits

arenaflex is committed to providing a supportive and inclusive work environment that fosters growth and development. As an Experienced Full Stack Data Analyst – Ancillary Revenue Data Scientist, you will have opportunities to:

  • Develop your skills and expertise in data analysis, machine learning, and data visualization

* Collaborate with cross-functional teams to drive business growth and improve operational efficiency *

Participate in training and development programs to enhance your knowledge and skills

* Contribute to the development of arenaflex's data analytics capabilities and drive business growth through data-driven insights

Compensation, Perks, and Benefits

arenaflex offers a competitive salary and a range of benefits, including:

Health insurance

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Retirement plan

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Paid time off

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Professional development opportunities

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Flexible work arrangements

How to Apply

If you are a motivated and experienced data analyst looking to join a dynamic team and contribute to driving business growth through data-driven insights, apply now! Click the link below to submit your application. Apply Now

Disclaimer

The above statements are intended to describe the general nature and level of work expected of the referred position; they are not intended to be a comprehensive list of all responsibilities, duties, and skills required of individuals in this role. Please note that obligations and assumptions about this position may be subject to change. Apply for this job

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