Data Engineer - Machine Learning Analytics

Data Engineer - Machine Learning Analytics

This job is no longer open
Our Vision
FLYR Labs is focused on the relentless application of advanced and intuitive technologies that help transportation leaders unlock their ultimate potential. 

Starting with airlines, we provide the Cirrus Revenue Operating System™ that reshapes how travel and transportations businesses plan their commercial operation. We displace legacy data, forecasting, pricing, and reporting solutions with a single enterprise SaaS platform that leverages the latest advancements in deep learning, cloud computing, and user experience.

Our hyper-accurate contextual forecasts enable the most effective scheduling, marketing, and leadership decisions while directly managing the pricing for billions of dollars worth of product and revenue.

Itinerary (About the role)

We are looking for an experienced Data Engineer to join our ML Analytics team. 
 
The ML Analytics team is dedicated to building the analytics tools, data, pipelines, reporting and metrics that allow us to effectively and efficiently evaluate the effectiveness of our deep learning-based pricing and forecast models.
 
You are a highly curious, detail-oriented, independent data expert. You thrive on building data pipelines and ETLs, managing our team’s data warehousing needs end-to-end. You are a highly competent communicator towards both technical and non-technical audiences. If you’re happiest learning new, challenging domains, then FLYR has what you are looking for.
 
You will be joining a dedicated team of Data Scientists, Data Analysts and ML Engineers responsible for the development of our ML model validation tooling and metrics that enable FLYR to decide where we should invest more time and attention in our algorithms.

What will your journey look like? (Responsibilities)

    • Develop and implement best practices and standardized, repeatable processes for implementing enterprise-grade data transformation/ingest pipelines, with an eye toward scalability
    • Design and own the data architecture that enables Data Scientists and other stakeholders to measure the performance of our live ML models in production
    • Develop new product feature capabilities in a robust and scalable data-centric infrastructure using Python, Google BigQuery, Apache Beam / Google Dataflow, and Kubernetes
    • Work closely with Data Scientists and ML Engineers to design and implement data model changes and to communicate opportunities for tool improvements

What can you bring on this trip? (Qualifications)

    • Quantitative work/education background (computer science or equivalent)
    • Ability to ship production-quality Python code
    • 5+ years of hands-on experience with cloud computing services and BigQuery
    • 5+ years of experience building and operating data transformation pipelines
    • Advanced SQL. You know your way around analytical and aggregate functions, complex joins, window functions, and are confident in wrangling all types of data in SQL
    • Ability to leverage cloud computing services to build and maintain data transformation pipelines
    • Experience with data warehouses, ETL automation, BI visualization tools, and cloud-based data management tools
    • Experience with parallel data processing frameworks such as Apache Beam, Spark and Hive
    • Ability to clearly communicate status, blockers, risks, and dependencies to FLYR and customer stakeholders

In-Flight Amenities (Perks & Benefits)

    • Equity in Series C startup with high growth potential
    • Comprehensive healthcare plans (Choice of PPO & HMO available)
    • Generous PTO policy and flexible working arrangements
    • 401K with company match
    • Free Breakfast/Lunch (in office)
    • Uber Eats - $20/week
    • 100% Paid Parental Leave for 12 Weeks
    • $300 Home office set-up stipend (one time)
    • Dog Friendly Offices
Our Commitment to Equality
At FLYR, we are proud to be an equal opportunity workplace and embrace a commitment to have our teams better reflect the world around us as we scale the business.
This job is no longer open
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