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Remote Sports Data Collection Jobs in California

Junior Data Analyst

Los Angeles, CA · On-site +1

$26 - $37/hr

Data Collection and Management: * Gather and preprocess data from various sources, including ... Remote-based with potential for hybrid work arrangements. * Full-time position with standard ...

... remote Responsibilities Analyze data on the experiences of customers, articulate and visualize their overall experience and gain actionable insights from them Drive, own, and execute data collection ...

Design, develop, and maintain databases and data collection systems to optimize data quality and ... Remote Work Requirements * Hard-wired ethernet connection. * Safe and secure workspace. * Ability ...

Interview: remote Questions that need to be answered by candidate: Submission summaries need to ... Create new experimental frameworks to collect data, build tools to automate data collection

Interview:- remote QUESTIONS THAT NEED TO BE ANSWERED BY CANDIDATE: Submission summaries need to ... Create new experimental frameworks to collect data, build tools to automate data collection

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ...

Tennis Data Scientist

San Francisco, CA · On-site +1

$135K - $190K/yr

Company Description Swish Analytics is a sports analytics, betting and fantasy startup building the ... This position is remote from the USA. Duties: * Ideate, develop and improve machine learning and ...

GIS Analyst I

Auburn, CA · On-site +1

$25 - $31/hr

Works with lidar, imagery, and other remote sensing datasets to extract relevant geospatial information. Field Data Collection and Integration * Assists in field data collection using mobile GIS ...

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Remote Sports Data Collection information

What are the key skills and qualifications needed to thrive as a Remote Sports Data Collection Specialist, and why are they important?

To thrive as a Remote Sports Data Collection Specialist, you need a keen attention to detail, strong analytical skills, and a solid understanding of various sports, often supported by relevant experience or education in sports management or statistics. Familiarity with specialized data entry software, live scoring platforms, and sometimes certifications in data analysis tools are typically required. Exceptional time management, reliability, and clear communication help professionals excel, especially when working independently or coordinating with global teams. These skills are crucial for ensuring the accuracy, timeliness, and reliability of sports data that powers analytics, broadcasts, and betting markets.

What are some common challenges faced in remote sports data collection roles, and how can they be addressed?

One common challenge in remote sports data collection is ensuring real-time accuracy while working independently, often under tight deadlines during live events. Technical issues such as unstable internet connections or software glitches can also occur, potentially impacting data integrity. To address these challenges, it’s important to have a reliable internet setup, stay familiar with the data collection platform, and maintain clear communication with team supervisors. Proactively preparing backup tools and following established protocols can further help ensure data quality and timely delivery.

What is remote sports data collection?

Remote sports data collection involves gathering, recording, and sometimes analyzing sports-related statistics and information from a distance, typically using digital tools and platforms. Professionals in this role may watch live broadcasts, access official feeds, or use specialized software to collect data such as scores, player statistics, and game events. This data is then used by organizations like sports analytics firms, betting companies, and media outlets. The job allows for flexible work locations and often requires strong attention to detail and a solid understanding of the sport being covered.

What is the difference between Remote Sports Data Collection vs Remote Sports Data Entry?

AspectRemote Sports Data CollectionRemote Sports Data Entry
CredentialsBasic data handling skills, familiarity with sports statisticsTyping skills, attention to detail, basic computer skills
Work EnvironmentFieldwork, online platforms, live event coverageHome-based, computer-focused tasks
Employer & Industry UsageSports analytics companies, media outlets, sports organizationsData management firms, sports websites, research companies
Search & Comparison IntentUnderstanding roles involving sports data collection and analysisClarifying data entry tasks related to sports information

Remote Sports Data Collection involves gathering live or recorded sports data, often requiring fieldwork or online monitoring during events. In contrast, Remote Sports Data Entry focuses on inputting sports data into databases from existing sources. Both roles support sports industry operations but differ in scope and environment.

What are the most commonly searched types of Sports Data Collection jobs in California? The most popular types of Sports Data Collection jobs in California are:
What are popular job titles related to Remote Sports Data Collection jobs in California? For Remote Sports Data Collection jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Sports Data Collection jobs in California look for? The top searched job categories for Remote Sports Data Collection jobs in California are:
What cities in California are hiring for Remote Sports Data Collection jobs? Cities in California with the most Remote Sports Data Collection job openings:
Sports Data Analyst

Sports Data Analyst

Swish Analytics

San Francisco, CA • On-site, Remote

Full-time

Posted yesterday


Job description

Company Description
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Duties:
  • Work closely with Data Scientists and Engineers to diagnose and treat data pipeline integrity issues
  • Detect data inaccuracies such as missing, out of range or otherwise incorrect on-field data
  • Source origins of data inaccuracies through data pipeline dependencies and python code base
  • Define data validation tests to flag future game errors
  • Research accurate roster active statuses, primary positions and game participation
  • Validate data changes after logic updates
  • Production model feature deep dives to explain project market lines
  • Clearly document findings
  • Develop intimate familiarity with existing databases and construct metadata references
  • With guidance, support lead Data Scientists in feature development and model analysis

Requirements:
  • Bachelor's Degree in Computer Science, Data Science or similar major
  • Minimum of 1 year of experience in football data analysis
  • Deep knowledge of football, basketball or baseball; including roster compositions of professional and college teams, general gameplay strategies, and typical in-game scenarios
  • Data Extraction, Wrangling and Analysis in Python
  • Strong SQL querying skills
  • Attention to detail

Preferred:
  • Strong Python data management programming skills
  • Data Visualization experience with a user application like Streamlit
  • Deep knowledge of a second sport including football, basketball, baseball, hockey or tennis
  • Exposure to the data science process and tech stack
  • Anomaly Detection Techniques

Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Data Science Role NFL Team Locations San Francisco, CA - Remote Remote status Fully Remote