Data Scientist (Generative AI, Cloud Deployment & Advanced NLP Expertise)

Job Summary

Synechron is seeking a highly skilled Data Scientist to lead innovative projects leveraging advanced AI/ML models, particularly in generative AI techniques. In this role, you will design, develop, and deploy AI solutions integrating cloud services and enterprise architectures to solve complex problems. Your expertise will support the organization’s digital transformation efforts by delivering data-driven insights, developing generative AI applications, and integrating cutting-edge AI tooling within enterprise environments — ultimately helping to accelerate business value and technological leadership.

Software Requirements

Required Skills:

• Strong proficiency in Python, Java, and relevant AI frameworks
• Extensive experience with Generative AI models, including OpenAI GPT, Codex, or similar platforms
• Practical knowledge of cloud services for AI, such as AWS AI tools (Lex, Comprehend, Rekognition) and cloud infrastructure deployment
• Experience in deploying solutions on cloud platforms (AWS, GCP, Azure)
• Familiarity with version control systems (Git, GitHub)
• Experience with AI development tooling including GitHub Copilot, AWS CodeWhisperer, or other AI code assistance tools
• Skill in designing and managing data pipelines and eliminating bias in training datasets

Preferred Skills:

• Experience with open-source ML libraries (TensorFlow, PyTorch)
• Knowledge of infrastructure as code (Terraform, CloudFormation) for deploying AI solutions
• Experience with static code analysis and secure coding practices for AI/ML systems

Overall Responsibilities

• Lead the development, deployment, and optimization of AI/ML models, with an emphasis on generative AI capabilities
• Design and implement scalable data pipelines and workflows to support AI model training and inference
• Advising on innovative AI approaches to improve operational efficiency and generate new business insights
• Integrate AI solutions within existing enterprise architectures, utilizing cloud services and microservices best practices
• Mentor data science and development teams, promoting best practices in model development, testing, and deployment
• Stay current with emerging AI research, tools, and industry use-cases, infusing them into organizational projects
• Collaborate with stakeholders to define requirements, translate business problems into AI solutions, and ensure alignment with business goals
• Ensure AI solutions are developed and maintained in compliance with security, privacy, and ethical standards
• Document processes, models, and performance metrics for ongoing improvement and audit readiness

Technical Skills (By Category)

• Programming Languages:

  • Essential: Python, Java
  • Preferred: R, C++, or relevant scripting languages for automation and data processing

• Frameworks & Libraries:

  • Essential: PyTorch, TensorFlow, Transformers (e.g., Hugging Face), OpenAI SDKs
  • Preferred: Scikit-learn, Keras, NLTK for NLP tasks

• AI/ML Concepts & Models:

  • Essential: Generative AI models (GPT, GPT-3, Codex), Transformer architectures, Large Language Models (LLMs)
  • Preferred: Fine-tuning, prompt engineering, model explainability, bias mitigation techniques

• Cloud & Infrastructure:

  • Essential: AWS (SageMaker, Lex, Comprehend, Rekognition), Azure, GCP AI services
  • Preferred: Managed ML services, containerization (Docker), Kubernetes, serverless deployment (Lambda, Cloud Functions)

• Data & Data Management:

  • Essential: Data pipelines, feature engineering, dataset management
  • Preferred: Data versioning, bias detection, data augmentation techniques

• DevOps & CI/CD:

  • Essential: GitHub Actions, Jenkins, AWS CodePipeline, automation of deployment pipelines
  • Preferred: Terraform, CloudFormation, infrastructure automation

Experience Requirements

• 7+ years of full-cycle software development experience with a focus on AI/ML and data science
• Proven track record of delivering enterprise-grade AI solutions, especially in generative AI applications
• Strong expertise in deploying AI models in cloud environments and managing AI infrastructure
• Experience working within cross-functional teams, translating business needs into AI solutions
• Industry experience in finance, healthcare, or enterprise digital transformation projects is an advantage
• Alternative pathways include extensive research, open-source contributions, or leadership in AI innovation projects

Day-to-Day Activities

• Architect and develop advanced AI/ML models, focusing on generative AI and NLP solutions
• Build and maintain scalable data pipelines and training workflows
• Collaborate with product teams and stakeholders to understand complex business problems and propose AI-based solutions
• Fine-tune models, improve inference efficiency, and deploy solutions on cloud platforms
• Integrate AI tools with existing cloud, microservices, and enterprise platforms
• Monitor model performance and data quality, iterating to improve effectiveness
• Share insights, conduct AI research, and educate teams on emerging AI developments
• Partake in code reviews, testing, and documentation of models and workflows

Qualifications

• Master’s or PhD in Data Science, Computer Science, AI, Machine Learning, or related fields
• Relevant certifications in AI/ML platforms, cloud solutions, or data science (preferred)
• Demonstrated experience with producing or deploying large language models, generative AI systems, or NLP solutions in production environments

Professional Competencies

• Strong analytical thinking and problem-solving skills, with the ability to translate data into actionable insights
• Excellent communication skills, able to articulate complex AI concepts to non-technical stakeholders
• Leadership abilities to guide teams and influence best practices in AI/ML deployment
• High adaptability, eagerness to learn new tools, and stay updated with AI research
• Ethical mindset and awareness of AI fairness, bias, and privacy considerations
• Effective time and project management skills, balancing innovation with deliverables

S​YNECHRON’S DIVERSITY & INCLUSION STATEMENT
 

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

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