Python Developer with Data Structure

specialty in lieu of every year of education.

• All applicants authorized to work in the United States are encouraged to apply
• Candidate must live within commuting distance of Richmond, VA OR Pennington, NJ OR Plano, Tx OR Charlotte, NC OR be willing to relocate. This is an onsite position. Travel within the US may be required.
• At least 4 years of experience in Information Technology
• At least 3 years of experience as Core Python Developer with Data Structures, Stacks, Queues, Linked list OOPS concepts,
• At least 3 years of experience in Creating large-scale data processing pipelines to help developers build and train novel machine learning algorithms.
• At least 3 years of experience in developing, test and maintain high-quality software using Python programming language.
• At least 3 years of experience in Cloud platforms (e.g., GCP, Azure) and their AI services.
• At least 2 years of experience in developing ML, NLP Deep learning models
• At least 2 years of Experience in working With Derivatives and Capital Markets
• Ability to write clean and reusable code that can be easily maintained and scaled.

Preferred Qualifications:

• Experience in LLM, Generative AI (developing capabilities or Dev/Ops)
• Participation experience in code reviews, ensure code quality and identify areas for improvement to implement practical solutions.
• Debugging codes when required and troubleshooting any Python-related queries.
• Experience in working with Multi cloud environment such as, GCP, AWS, Azure
• Excellent problem-solving skills and ability to address complex technical challenges.
• Effective communication skills to collaborate with cross-functional teams and stakeholders.
• High Impact client communication
• Domain experience in Banking, Finance, Capital Markets

The job may entail extensive travel. The job may also entail sitting as well as working at a computer for extended periods of time. Candidates should be able to effectively communicate by telephone, email, and face to face.