Position Requirements
Job Description: We are seeking a highly motivated and enthusiastic AI/ML Analytics
Engineer/Analyst to join our dynamic team.
Key Responsibilities:
• Assist in the development and implementation of machine learning models and algorithms.
• Work closely with senior data scientists and AI/ML engineers to understand project
requirements and deliverables.
• Utilize statistical and machine learning techniques to analyze and interpret complex data
sets.
• Stay updated with the latest advancements in AI/ML technologies and methodologies.
• Collaborate with cross-functional teams to support various AI/ML initiatives.
Qualifications:
• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related
field.
• Strong understanding of machine learning concepts and algorithms.
Preferred Skills:
• Experience in machine learning techniques such as Regression, Classification, Predictive
modeling, Clustering, Deep Learning stack, NLP using python
• Familiarity with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn).
• Experience with data visualization tools (e.g., Matplotlib, Seaborn, Quicksight).
• Knowledge of deep learning frameworks (e.g., TensorFlow, Keras, PyTorch).
• Familiarity with cloud platforms (e.g., AWS, Azure).
• Experience with version control systems (e.g., Git).
• Awareness about databases – DynamoDB OpenSearch.

Diversity, Equity and Inclusion:

With our expanding global presence, cross-cultural insight and competence are essential for our ongoing success. We believe that a diverse workforce contributes different perspectives and creative ideas that enable us to continue to improve every day. Race, gender, ethnicity, country of origin, age, personal style, sexual orientation, physical ability, religion, life experiences and many more factors contribute to this diversity.

We take ongoing action to improve the diversity of our workforce by:

• Ensuring leadership involvement and ownership
• Attracting and retaining diverse talent at all levels
• Fostering a globally aware, inclusive culture
• Ensuring our practices are fair and non-discriminatory