Data Scientist (Data Analyst, Python, SQL, Database)

1. Advanced Machine Learning and Statistics

• Deep understanding of machine learning algorithms, including both supervised and unsupervised learning.
• Proficiency in advanced techniques such as ensemble methods, deep learning, and reinforcement learning, with over 3-5 years of experience in the data science field or related fields.
• Strong skills in statistical modeling, coupled with experience in model deployment (considered a plus).

2. Programming Skills

• Strong background in Python, with proficiency in packages like scikit-learn, TensorFlow, or PyTorch.
• Capability to create and manage APIs effectively.

3. Domain Knowledge and Communication

• Engaged follower of individual athletic events with strong analytical skills for evaluating performance, showcasing a passion for sports.
• Proficiency in English, covering all four skills: listening, speaking, reading, and writing, to ensure effective communication within our diverse team.

4. Data Handling Capabilities

• Proven ability to handle and process large volumes of data, along with competence in managing data pipelines and warehouses.

5. Portfolio and Experience

• A robust portfolio that demonstrates relevant projects, achievements, and a clear indication of problem-solving capabilities.
• Previous experience in a related field, highlighting the candidate's ability to contribute to innovative solutions and a deep understanding of athletics analytics.