Software Engineer, Machine Learning

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Written by AI from the job title and company, not by National Basketball Association (NBA), so some details may not match this job. The employer's own page has the real description.

Job Overview

The Software Engineer, Machine Learning at the National Basketball Association (NBA) will be responsible for designing, developing, and deploying machine learning models and algorithms that enhance the NBA's data analysis capabilities. This role requires collaboration with various teams to ensure the interpretation of complex data is effective and actionable, driving innovative solutions that align with the NBA's strategic goals. Responsibilities include optimizing existing algorithms, conducting research on cutting-edge technologies, and translating business requirements into technological solutions that advance analytics within the league.

Job Responsibilities

• Design, implement, and maintain machine learning models to support analytics initiatives within the NBA.
• Collaborate with data scientists and analysts to understand data needs and develop scalable solutions.
• Optimize existing algorithms to improve performance and enhance accuracy in predictive modeling.
• Conduct exploratory data analysis to identify trends, patterns, and insights from large datasets.
• Stay up-to-date with the latest machine learning techniques and technologies, integrating them into current practices.
• Participate in code reviews and provide constructive feedback to maintain high-quality code standards.
• Document processes and create training materials to support team knowledge sharing.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; Master’s degree preferred.
• 3+ years of professional experience in software engineering with a focus on machine learning.
• Proficiency in programming languages such as Python, Java, or C++.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Solid understanding of algorithms, data structures, and software design principles.
• Familiarity with data querying languages (e.g., SQL) and big data technologies (e.g., Hadoop, Spark).
• Strong analytical and problem-solving skills.
• Excellent communication skills with the ability to explain complex data concepts to non-technical stakeholders.

Technologies & Tools

The Software Engineer, Machine Learning will utilize a variety of technologies and tools including but not limited to Python for algorithm development, TensorFlow and PyTorch for machine learning model implementation, SQL for data manipulation, and cloud platforms such as AWS or Google Cloud for scalable data processing. Familiarity with version control systems like Git and collaboration tools such as JIRA will also be crucial for effective project management and team communication.

Ideal Candidates

Ideal candidates for this position will possess a strong technical foundation complemented by creativity and a passion for sports analytics. They will demonstrate a deep curiosity for exploring data-driven insights and a commitment to delivering exceptional results. Furthermore, they should be proactive collaborators, comfortable working in a dynamic environment, and capable of adapting to evolving business needs. A keen interest in basketball, combined with the technical expertise necessary to influence decision-making through innovative machine learning solutions, will set them apart.