Sr Machine Learning Engineer

at  Academy Sports

Come work at a place where we take pride in creating a workplace environment that values hard work, commitment, and growth.

JOB DESCRIPTION:

Education:

• Bachelor’s degree in Computer Science, Data Science, Information Systems/Sciences, Business Analytics, Machine Learning, Information Technology Management or relevant field of study required
• Master’s degree preferred

WORK EXPERIENCES:

• 3+ years of experience in machine learning and data science, with a focus on developing, customizing, and deploying machine learning models in production environments.
• 2+ years of experience in core Python programming

SKILLS:

• Proficiency in Python(Preferred) or R, emphasizing machine learning libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.
• Advanced skills in mathematics, probability, statistical methods, and SQL
• Expertise in supervised and unsupervised learning, including regression, classification, clustering, and deep learning techniques
• Experience with hyperparameter tuning, model optimization, and performance evaluation.
• Ability to translate business requirements into data science projects and communicate findings effectively to stakeholders using an unbiased, data-driven approach
• Self-motivated and able to work independently and within a team setting
• Analytical, with strong problem-solving abilities and creative resolution skills
• Ability to remain organized, pay strict attention to detail, and meet critical deadlines with high volume, fast-paced environment

PHYSICAL REQUIREMENTS & ATTENDANCE:

• Regular attendance required
• Acceptable level of hearing and vision to perform job duties
• Adhere to company work hours, policies, procedures and rules governing professional staff behavior
  Full time

• Design, develop, and deploy scalable and efficient machine learning models for various applications, including but not limited to predictive analytics, natural language processing.
• Evaluate and implement state-of-the-art machine learning algorithms to address business challenges such as customer LTV/retention/churn prediction, personalized recommendations.
• Lead the resolution of complex challenges by framing problems, hypothesizing solutions, and recommending actions that emphasizing advanced machine learning applications
• Apply MLOps principles and practices throughout the machine learning lifecycle, including model deployment and monitoring.
• Collaborate with product, marketing, finance, and IT teams to understand business needs and deliver machine learning solutions that drive value.
• Develop tools that assist and partner with data scientists in streamlining the process of creating and prototyping machine learning models (e.g. features store)
• Stay updated with the latest advancements in machine learning and artificial intelligence research, incorporating new methodologies into existing processes.
• Develop a thorough understanding of Academy’s policies, procedures and safety rules
• Duties may change; team members may be required to perform other duties as assigned