AI/ML Architect

Job Description: We are seeking a talented and experienced AI/ML Data Analyst to join our [AI/ML team/data team]. As a crucial member of our team, you will be responsible for extracting, cleaning, and analyzing large datasets to generate insights and support our AI/ML initiatives. You will work closely with data engineers, data scientists, and other stakeholders to ensure the quality and reliability of data used in our machine learning models.

Key Responsibilities:

• Collaborate with cross-functional teams to understand data requirements for AI/ML projects
• Acquire, clean, and preprocess data from various sources to prepare it for analysis and modeling
• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies in the data
• Design and implement data pipelines for efficient data processing and model training
• Develop and maintain documentation for data processes, datasets, and models
• Collaborate with data scientists to design and evaluate machine learning models
• Monitor and assess the performance of machine learning models and make recommendations for improvements
• Work with IT and engineering teams to ensure data infrastructure meets the requirements of AI/ML projects
• Stay up-to-date with industry trends and best practices in AI/ML and data analysis

Qualifications:

• Bachelor's degree in Computer Science, Data Science, Statistics, or a related field
• 4-5 years of experience in data analysis, with a focus on AI/ML projects
• Proficiency in programming languages like Python, R, and SQL
• Strong knowledge of data manipulation, cleaning, and preprocessing techniques
• Experience with data visualization tools (e.g., Tableau, Power BI)
• Familiarity with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch)
• Strong analytical and problem-solving skills
• Excellent communication and collaboration skills
• [Optional] Experience with big data technologies (e.g., Hadoop, Spark)

Preferred Qualifications:

• Degree in Data Science, Machine Learning, or a related field
• Experience with cloud platforms (e.g., AWS, Azure, GCP)
• Knowledge of advanced statistical techniques and modeling