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

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.