Data Scientist - Gen AI Lead Consultant SUNTRUST|SunTrust Bank

Infosys • Dallas, GA

3d

About The Position

Infosys is seeking an accomplished GenAI Lead Consultant with expertise in Data Science, Machine Learning (ML), and Generative AI to drive transformative solutions for our financial services clients. This role combines deep technical proficiency, functional domain knowledge, and robust pre-sales expertise to lead complex AI/ML projects, deliver innovative solutions, and build strong client relationships. The ideal candidate will excel in the following areas: Design, development, and deployment of advanced machine learning and generative AI models (e.g., LLMs, GANs, diffusion models) to address complex financial services challenges; Performing hands-on data analysis, feature engineering, and model optimization to deliver high-performance solutions; Leading the creation and submission of high-quality responses to Requests for Proposals (RFPs), Requests for Information (RFIs), and other client solicitations, clearly articulating technical and business value.

Requirements

• Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• Candidate must live within commuting distance of Dallas, TX, Charlotte, NC OR Atlanta, GA or be willing to relocate. This position may require travel in the US.
• At least 7 years of experience in Information Technology.
• Applicants authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time.
• At least 4 years of experience in Information Technology in Data Science, Analytics and Machine Learning.
• Proven expertise in generative AI technologies (e.g., GPT, BERT, Stable Diffusion) and their application in financial services.
• At least 4 years of pre-sales experience, including responding to RFPs/RFIs, proactive client engagement, delivering client demos, and preparing presentations.
• Proficiency in Python, R, or Scala and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face, LangChain).
• Expertise in cloud platforms (AWS, Azure, GCP) and MLOps tools (e.g., Kubeflow, MLflow, SageMaker).
• Experience with big data technologies (e.g., Hadoop, Spark, Snowflake) and databases (SQL, NoSQL).
• Knowledge of financial modeling, time-series analysis, and risk analytics.
• Strong experience in drafting and responding to RFPs, RFIs, and other proposal documents with a focus on technical and business alignment.
• Deep knowledge of financial services domains, including risk management, fraud detection, customer analytics, and regulatory compliance.
• Ability to communicate complex technical concepts to non-technical stakeholders effectively.

Nice To Haves

• Master’s or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• At least 10 years of experience in data science and machine learning, with at least 5 years in the financial services industry.
• Demonstrated success in crafting high-quality slide decks and pitch presentations for C-suite audiences using PowerPoint or similar tools.
• Experience working with financial services clients in banking, insurance, wealth management, or fintech.
• Familiarity with financial regulations (e.g., AML, KYC, IFRS 9, Basel III).
• Certifications in cloud platforms (e.g., AWS Certified Machine Learning, Azure AI Engineer) or data science (e.g., TensorFlow Developer Certificate).
• Published research, patents, or contributions to open-source AI/ML projects
• Proven ability to deliver engaging client demos and POCs that demonstrate solution feasibility and value.
• Exceptional presentation skills, with advanced proficiency in creating visually compelling PowerPoint decks and executive-level materials.
• Ability to proactively engage clients, identify opportunities, and build strategic relationships.

Responsibilities

• Design, development, and deployment of advanced machine learning and generative AI models (e.g., LLMs, GANs, diffusion models) to address complex financial services challenges
• Performing hands-on data analysis, feature engineering, and model optimization to deliver high-performance solutions
• Leading the creation and submission of high-quality responses to Requests for Proposals (RFPs), Requests for Information (RFIs), and other client solicitations, clearly articulating technical and business value

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees