Data Scientist
The role of a Data Scientist at Passive Picks goes beyond traditional data analysis. Here, you'll be diving deep into vast datasets, extracting not just numbers, but stories, patterns, and game-changing insights that will fuel our prediction algorithms. Every dataset you encounter will be a puzzle, waiting for you to unravel its intricacies and deliver actionable insights. In collaboration with our engineering team, you'll be developing predictive models, integrating machine learning algorithms, and constantly pushing the envelope of what's possible in sports prediction. Staying updated with the latest in data science methodologies, tools, and techniques, you'll be on the front lines, ensuring that Passive Picks remains at the pinnacle of sports handicapping through data-driven excellence.
Your role
- Extract, clean, and preprocess data from various sources to make it suitable for analysis.
- Use statistical and machine learning techniques to discover patterns, correlations, and insights within the data.
- Build, test, and refine predictive models for sports outcomes.
- Collaborate with the algorithm engineering team to integrate models and insights into the main algorithmic pipeline.
- Constantly monitor the performance of deployed models, refining and recalibrating when necessary.
- Stay abreast of the latest advancements in data science, machine learning, and statistical modeling.
- Communicate findings and insights to both technical and non-technical stakeholders within the company.
- Contribute to research and development efforts, pushing the boundaries of what’s possible within sports analytics.
- Work closely with the data engineering team to ensure the efficient flow and storage of data.
Your team
Join our data-focused team, where numbers tell the story and drive our successes.
Requirements
Who are you?
- Master’s or Ph.D. in Data Science, Statistics, Applied Mathematics, or a related field.
- Minimum of 4 years of experience in data analysis, modeling, and predictive analytics.
- Proficient in data manipulation tools and programming languages such as Python, R, and SQL.
- Expertise in machine learning libraries like scikit-learn, TensorFlow, or similar.
- Strong foundational knowledge in statistical methods and hypothesis testing.
- Demonstrated ability to translate complex data-driven insights into actionable recommendations.
- Familiarity with big data platforms and tools such as Hadoop and Spark is a plus.
- Excellent communication skills, both verbal and written.
- A genuine passion for sports and a curiosity to understand the data behind the game.
Benefits
- Competitive salary with attractive commission structure
- Continuous professional development
- Flourish in a culture of trust, ownership, and standard of excellence
- Getting-things-done environment with sharp and knowledgeable colleagues
- Minimal time spent in meetings
- Work (partly or fully) remote whenever you want
- Enjoy flexible working hours and holidays wishes (paid and extra unpaid leave)
- Company-wide outings & events
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