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Remote Data Science Sports Jobs in Edison, NJ (NOW HIRING)

Our full-stack Data Science Team uses Python for research and development. Our wide range of ... Due to the remote nature of this role, we are unable to provide visa sponsorship.

Remote Duration 4-6 months The RBQM Data Scientist supports central monitoring and risk-based quality management (RBQM) for clinical trials. This role focuses on implementing and running pre-defined ...

Data Scientist

New York, NY ยท On-site +1

If you are passionate about concerts, sports, or theater, and want to see your skills and ... BA/BS in a quantitative field such as Statistics, Computer Science, Engineering, Mathematics, or ...

Lead Data Scientist

New York, NY ยท On-site +1

$144K - $250K/yr

Bachelor's Degree in Statistics, Mathematics, Engineering, Data Science, Computer Science, or ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

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Remote Data Science Sports information

What are the key skills and qualifications needed to thrive as a remote data science sports professional?

To thrive as a Remote Data Science Sports professional, you need a strong background in statistics, data analysis, and sports knowledge, often supported by a degree in mathematics, statistics, computer science, or a related field. Familiarity with programming languages such as Python or R, proficiency in data visualization tools, and experience with machine learning frameworks are typically required. Excellent problem-solving abilities, communication skills, and self-motivation are crucial soft skills for collaborating remotely and translating complex data into actionable insights. These skills ensure accurate sports data modeling, effective remote teamwork, and valuable contributions to decision-making in sports organizations.

What is the difference between Remote Data Science Sports vs Remote Data Analysis Sports?

AspectRemote Data Science SportsRemote Data Analysis Sports
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; programming skills in Python/RBachelor's in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL, and visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves modeling and machine learningData interpretation, reporting, and visualization, often in business contexts
Employer & Industry UsageTech companies, sports analytics firms, media outletsSports teams, media companies, sports analytics agencies

Remote Data Science Sports involves advanced modeling, machine learning, and statistical analysis, requiring higher technical credentials. Remote Data Analysis Sports focuses on interpreting data, creating reports, and visualizations. Both roles are common in sports industry analytics but differ in complexity and technical depth.

How do remote data science professionals in the sports industry typically collaborate with coaches and analysts to turn data insights into actionable strategies?

Remote data science professionals in the sports industry often work closely with coaches, analysts, and other stakeholders through regular virtual meetings and collaborative platforms. They translate complex data findings into intuitive visualizations and reports, making it easier for non-technical team members to understand and apply insights. Communication and responsiveness are key, as data scientists may need to quickly adjust analyses based on feedback or new priorities from the sports staff. Building strong relationships and maintaining clear channels of communication help ensure that data-driven recommendations are effectively integrated into training, game strategies, and player development.

What is a remote data science sports job?

A remote data science sports job involves analyzing sports-related data to extract insights, build predictive models, and support decision-making, all while working from a location outside of a traditional office, typically from home. Professionals in this role use statistical methods, programming, and machine learning to evaluate player performance, game strategies, or fan engagement. Their work helps sports teams, leagues, media companies, and betting firms make evidence-based decisions. Remote positions offer flexibility and often require strong communication skills to collaborate with teams virtually. The demand for these roles is growing as the sports industry increasingly relies on data-driven strategies.
What are popular job titles related to Remote Data Science Sports jobs in Edison, NJ? For Remote Data Science Sports jobs in Edison, NJ, the most frequently searched job titles are:
What job categories do people searching Remote Data Science Sports jobs in Edison, NJ look for? The top searched job categories for Remote Data Science Sports jobs in Edison, NJ are:

Data Science Specialist

Adidev Technologies Inc

Manhattan, NY โ€ข Remote

Full-time

Re-posted 18 days ago


Job description

Adidev Technologies Inc 

www.adidevtechnologies.com

URGENT HIRE - HIRING PROCESS - 24-48 HOURS!

Adidev Technologies is seeking 1-2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment.

If you are looking for a new challenge and are ready to make an impact on a growing team, then this will be a perfect fit. As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and debugging large-scale applications for one of our well-known clients.

Adidev Technologies is a growing software consulting company that is constantly expanding. As we are working with renowned clients and ready to take on new ones, we are seeking brilliant software engineers. Not only do we offer a great team to work with, but we also offer you an opportunity to make an immediate impact and get rewarded accordingly

 

Job Description

  • Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation systems, environmental systems, and/or agronomic problems.
  • Strong foundation in Python programming in a cloud environment.
  • Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills
  • Expertise in data wrangling using SQL,
  • Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes
  • Fluency in querying/extracting/aggregating data via SQL scripting.
  • Extract, load and transform data (ETL) from structured and unstructured sources
  • Apply Natural Language Processing and Computer Vision to solve business use cases,
  • Strong skills in scientific data analyses, modeling, visualization and communication of results.
  • Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction
  • Ph.D., M.S. or B.S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote Sensing Science, Environmental Sciences, Computational Astronomy or related scientific discipline


Must  have 

  • Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others)
  • Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization)
  • Classification (K-means, Hierarchical, Latent Class, DBScan, SVM)
  • Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.)
  • Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.)
  • Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras
  • Machine Learning algorithms? Neural Networks, Naïve Bayes, Bagging & Boosting, Random Forest
  • Distributed computing tools and cloud technology (AWS)

QUALIFICATIONS

  • Degree in Data Science, Computer Science, Engineering, Math, or Statistics preferred
  • At least 2 yrs of relevant experience in Data Science


SKILLS

  • SQL, statistical modeling, Feature engineering, Data visualization, Deploying models to production, Python programming, AWS, Domains(Healthcare/ Manufacturing/ Marketing/ Financial/ Telecommunication), powerbi/tableau, data warehouse

Benefits

  • Competitive Salary

  • Paid Relocation

  • Remote Support

  • Guaranteed Regular Salary Reviews

  • Job Type: W2 or Contract 1099 (full-time - 40 hours)

Employment Type: FULL_TIME