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Remote Football Data Science Jobs in Oregon (NOW HIRING)

Tebra

Data Engineer

OR · On-site +1

$114K - $137K/yr

You'll partner closely with Machine Learning Engineers, Data Scientists, and Software Engineers to ... Remote

Instacart

Senior Product Manager, Shopping Experience

OR · On-site +1

$126K - $166K/yr

You'll partner closely with design, research, engineering, data science, and go-to-market teams to ... We're a remote-friendly, fast-moving team that values clear communication, ownership, and ...

Upstart

Staff Data Analyst, Servicing

OR · On-site +1

$61K - $81K/yr

Degree in Economics, Statistics, Mathematics, Engineering, Data Science or other quantitative ... Remote Travel requirements As a digital first company, the majority of your work can be ...

Instacart

Senior Product Manager, AI

OR · On-site +1

$126K - $166K/yr

Partner with engineering and data science to scope experiments, manage backlogs, define KPIs and ... Remote

Natera

Medical Science Liaison

OR · On-site +1

Act as a subject matter expert on oncology disease states, clinical data, and the broader ... This is a remote, field-based position requiring daily use of a computer and the ability to travel ...

Natera

Medical Science Liaison

OR · On-site +1

Maintain an expert understanding of oncology disease states, clinical data, and the evolving ... This is a remote, field-based position requiring daily use of a computer and the ability to travel ...

NinjaTrader

Sr. Data Engineer

OR · On-site +1

$100K - $150K/yr

This role is remote-friendly and reports to the Manager, Data & Analytics Engineering. As a Sr. ... Bachelor's degree in Computer Science, Engineering, or a related field * 5+ years of experience in ...

YipitData

Senior Data Product Analyst

OR · On-site +1

Product New York, NY (Remote-Friendly) About the Role YipitData is making one of its most ambitious ... engineering, data science, market intelligence, alternative data, or a closely related field.

Five9

Data Center Engineer (in Atlanta, GA)

OR · On-site +1

Communicate and coordinate with remote hands in remote data centers, providing technical direction ... Bachelor of Science degree in Computer Science or equivalent experience

Upstart

Principal Applied Scientist

OR · On-site +1

Experience solving real-world machine learning or data science problems in a high-impact production ... Remote Time zone requirements The team operates on the East/West coast time zones.

Delaware Nation Industries

AI Developer/Engineer

OR · On-site +1

This is a fully-remote opportunity. The AI Developer/Engineer designs, develops, integrates, and ... This role works closely with software engineers, data scientists, product owners, and business ...

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All JobsFootball Data Science JobsRemote Football Data Science JobsRemote Football Data Science Jobs in Oregon

Remote Football Data Science information

What is the difference between Remote Football Data Science vs Remote Sports Data Analyst?

AspectRemote Football Data ScienceRemote Sports Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; knowledge of football analyticsDegree in Sports Management, Data Analysis, or related; familiarity with sports data
Work EnvironmentRemote, often collaborative with football teams or analytics firmsRemote or on-site, working with sports organizations or media outlets
Industry UsagePrimarily in football clubs, analytics companies, or sports tech startupsMedia, broadcasting, or sports organizations analyzing various sports

Remote Football Data Science focuses specifically on football analytics, requiring specialized knowledge of football metrics and data science skills. In contrast, Remote Sports Data Analysts work across multiple sports, analyzing diverse datasets. Both roles often work remotely and require similar analytical credentials, but their industry focus and specific expertise differ.

What does a remote football data science do in football?

A remote football data scientist analyzes football match data to identify patterns, improve team performance, and support strategic decisions. They use statistical tools, programming languages like Python or R, and data visualization techniques to interpret large datasets related to player performance, tactics, and game outcomes.

What are the most commonly searched types of Football Data Science jobs in Oregon?

The most popular types of Football Data Science jobs in Oregon are:

What are popular job titles related to Remote Football Data Science jobs in Oregon?

For Remote Football Data Science jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Remote Football Data Science jobs in Oregon look for?

The top searched job categories for Remote Football Data Science jobs in Oregon are:

What cities in Oregon are hiring for Remote Football Data Science jobs?

Cities in Oregon with the most Remote Football Data Science job openings:

Remote Football Data Science jobs near you

Data Engineer

Tebra

OR • On-site, Remote

$114K - $137K/yr

Full-time

Posted 26 days ago

Job description

About the Role

As a Data Engineer focused on AI/ML, you'll build, maintain, and optimize the data infrastructure that powers Tebra's intelligent features. You'll partner closely with Machine Learning Engineers, Data Scientists, and Software Engineers to transform complex healthcare data into high-quality datasets and real-time features that enable machine learning models.

This is a hands-on engineering role where you'll contribute to scalable data pipelines, improve data quality, and help ensure our AI systems are powered by reliable, performant, and well-governed data. You'll work on modern data platforms and gain experience building solutions that support both model training and production inference.

Your Area of Focus
  • Design, build, and maintain scalable data pipelines for feature extraction, training data generation, and model monitoring.
  • Develop and enhance data systems that support analytics and machine learning workloads, including data lakehouse and feature store technologies.
  • Monitor production data pipelines, identify data quality issues or pipeline failures, and implement improvements to ensure reliability and freshness.
  • Participate in engineering design discussions and contribute to technical decisions around data architecture and pipeline implementation.
  • Build reusable data engineering components, including automated data quality checks, schema validation, and testing frameworks.
  • Translate business requirements into scalable data solutions that enable analytics and machine learning use cases.
  • Optimize SQL queries, Spark workloads, and data processing pipelines to improve performance and scalability.
  • Collaborate with ML Engineers and cross-functional partners to support MLOps best practices, including data versioning, lineage, and reproducibility.
  • Break down technical work into manageable tasks and deliver high-quality solutions within an agile team.
Your Professional Qualifications
  • 3+ years of professional experience in Data Engineering, Software Engineering, or a related field.
  • 2+ years of hands-on experience building and maintaining production data pipelines supporting analytics, reporting, or machine learning workloads.
  • Strong proficiency in Python and SQL with experience developing production-quality data pipelines.
  • Experience with modern data processing technologies such as Spark, Airflow, Kafka, or similar distributed data platforms.
  • Experience working with cloud-based data platforms such as Databricks, Snowflake, Delta Lake, or equivalent lakehouse technologies.
  • Understanding of data modeling, data warehousing, and data governance best practices.
  • Familiarity with machine learning data workflows, including training datasets, feature engineering, and data quality concepts.
  • Experience deploying and supporting production data pipelines with monitoring, testing, and CI/CD practices.
  • Strong problem-solving skills, attention to detail, and the ability to collaborate effectively across engineering and product teams.
  • Excellent communication skills and a desire to continuously learn new technologies and engineering practices.

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