Job Openings Data Scientist

About the job Data Scientist

  • Data Scientist
  • Hybrid, NY
  • Up to $125k base + 7-10% bonus

Responsibilities:

  • Collaborate with the client in the sport sector to understand their business objectives and challenges and ensure the delivery of high-quality analytics/data science solutions.
  • Design and build end to end machine learning solutions and statistical frameworks across fan behavior.
  • Own the full modeling lifecycle: problem framing, feature engineering, model selection, cross validation and hyperparameter tuning
  • Lead recurring analytical programs with a focus on reproducibility and automation.
  • Partner with data engineering to integrate model outputs into operational systems and stakeholder facing products.
  • Utilize your strong analytical and problem-solving skills to extract meaningful insights from data and contribute to data-driven decision-making.
  • Use variety of analytical tools (SQL, Python) and techniques (regression, decision trees, machine learning concepts etc.) to carry out analyses, create ML models and drive conclusions.
  • Support the integration of data science capabilities for the client to help solve tangible problems with measurable impact.
  • Contribute to the continuous improvement of analytics processes and methodologies.

Core Skills (Required):

  • Bachelor's degree in economics, mathematics, computer science/engineering, operations research or related analytics areas
  • 2+ years of hands-on experience in a data science role with a track record of shipping models into production.
  • Extremely proficient in SQL for robust data extraction and analysis.
  • Strong programming skills in Python.
  • Familiarity with Git and code/data version control.
  • Solid statistical foundation
  • Exposure to NLP techniques for processing unstructured survey data.
  • Excellent communication, problem-solving, and critical thinking skills.
  • Self-started and willingness to take on challenging initiatives
  • Effective time management and attention to detail
  • Familiarity with MLOps concepts

Qualifications (Preferred):

  • Master's degree in a relevant field (e.g., Data Science, Analytics, Business Analytics).