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Data Scientist

 

Job Title: Data Scientist
Experience Level: Developing Professional

About Us:

We are a leading football analytics company dedicated to revolutionizing the way football data is utilized. Our team is passionate about leveraging data to gain insights and enhance decision-making for football teams and enthusiasts. We thrive in a dynamic, fast-paced startup environment where innovation and drive are key.

Job Overview:

We are seeking a motivated and adaptable Data Scientist to join our analytics team. This role will support our mission by building, deploying, and refining data-driven models and processes, collaborating closely with data scientists, data engineers, and operations teams. The ideal candidate is skilled in core data science techniques and possesses a strong working knowledge of data infrastructure, workflow optimization, and scalable systems.

You will contribute to building sophisticated analytical solutions, model pipelines, and tools that enhance our capacity to handle large datasets and deliver insights effectively. This is a great opportunity to apply a broad skill set to support a mix of data science and system-oriented projects that fuel our analytics capabilities.

Key Responsibilities:

  • Model Development and Data Analysis:
    • Build and deploy analytical models to enhance our football analytics offerings, supporting real-time and complex insights.
    • Conduct advanced data analyses using statistical and machine learning methods, translating results into actionable insights for stakeholders.
    • Collaborate with other data scientists to refine modeling techniques and improve analytical workflows.
  • Data Preparation and Processing:
    • Design and maintain data processing pipelines that are reliable, scalable, and efficient.
    • Collaborate with data engineering and MLOps teams to ensure models can move seamlessly from development to production.
    • Optimize data flows to maintain consistency and performance, utilizing tools such as Databricks and Spark for efficient processing.
  • Supporting Model Deployment and Monitoring:
    • Work with MLOps and DevOps frameworks to deploy models reliably and with clear versioning standards.
    • Implement model monitoring and validation techniques, ensuring models remain robust and efficient post-deployment.
    • Assist in maintaining effective data quality and validation practices, integrating tools that keep our data and models aligned with expectations.

Qualifications:

  • Education: Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related field. Master’s is preferred.
  • Experience:
    • 2+ years of experience in data science, ideally with some exposure to data infrastructure or MLOps principles.
  • Technical Skills:
    • Proficient in Python, SQL, and skilled in data manipulation libraries (e.g., Pandas, PySpark, Polars).
    • Familiarity with MLOps tools such as MLFlow and Git version control, especially in a collaborative environment.
    • Experience with Docker or similar containerization technologies is a plus.
  • Other Skills:
    • Highly motivated, self-starter with excellent problem-solving skills.
    • Ability to work independently, own projects, and drive them across the finish line with minimal supervision.
    • Strong communication skills, capable of telling a compelling data-driven story to nontechnical stakeholders.
    • Passion for football and/or experience in the fantasy/betting market is highly desirable.

What We Offer:

  • Competitive salary and benefits package.
  • Opportunity to work in a cutting-edge industry with a passionate and driven team.
  • Flexible working environment with opportunities for remote work.
  • Professional development and growth opportunities.

*At this time, H-1B sponsorship or transfers are not available for this role.

 

Average salary estimate

$80000 / YEARLY (est.)
min
max
$70000K
$90000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

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