Join our innovative team and drive the future of AI/ML! We're seeking passionate individuals to transform data into actionable insights, impacting industries worldwide. Be part of a dynamic environment where your expertise will shape cutting-edge solutions and make a real difference.

As an Applied AI/ML Sr. Associate in our Data Science team, you will harness the power of machine learning to solve complex problems and enhance decision-making processes. You’ll collaborate with a diverse group of experts, fostering a culture of innovation and continuous learning. Together, we’ll push the boundaries of technology and create meaningful change.

Job responsibilities

- Develops and implements advanced machine learning models
- Analyzes large datasets to extract valuable insights
- Collaborates with cross-functional teams to integrate AI solutions
- Optimizes algorithms for performance and scalability
- Stays updated with the latest AI/ML trends and technologies
- Communicates findings and recommendations to stakeholders
- Mentors junior team members in AI/ML techniques
- Designs experiments to validate model effectiveness
- Ensures data quality and integrity in all analyses
- Contributes to the development of AI-driven products
- Documents processes and methodologies for future reference

Required qualifications, capabilities, and skills

- Bachelor’s degree in Computer Science, Data Science, or related field
- 3+ years of experience in machine learning implementation
- Proficiency in Python and machine learning libraries (e.g., TensorFlow, PyTorch)
- Strong understanding of data science principles and techniques
- Experience with data preprocessing and feature engineering
- Ability to work collaboratively in a team environment
- Excellent problem-solving and analytical skills
- Strong communication skills for technical and non-technical audiences

Preferred qualifications, capabilities, and skills

- Master’s degree in a relevant field
- Experience with cloud platforms (e.g., AWS, Azure)
- Familiarity with big data technologies (e.g., Hadoop, Spark)
- Knowledge of deep learning architectures
- Experience in deploying machine learning models in production
- Publications or contributions to AI/ML research
- Certification in AI/ML from a recognized institution