Data Scientist with Generative AI Experience

Job Title :- Data Scientist with Generative AI Experience Employment Type :- W2 Duration :- Long Term Visa Type :- All Visa applicable which are ready for W2 Location- Atlanta, GA (Day-1 Onsite) Job Description: Min of 6+ years of experience in data science, with at least 2 years focused on developing and deploying Generative AI models (e.g., GANs, transformers). – Proven track record of building and implementing machine learning models and generating insights from data in a business context. Technical Skills – Strong proficiency in machine learning frameworks and libraries, such as TensorFlow, PyTorch, and Scikit-Learn. – Expertise in Generative AI models (e.g., GANs, VAEs, and transformer-based models like GPT, BERT) with hands-on experience in training, fine-tuning, and deploying these models. – Proficient in data wrangling and preprocessing with tools like Pandas, NumPy, and experience in managing both structured and unstructured data. – Programming proficiency in Python and R, with experience in other languages (e.g., SQL) for data manipulation and retrieval. – Familiarity with cloud platforms (AWS, GCP, Azure) and their services for AI/ML, including model deployment and monitoring (e.g., AWS SageMaker, Google AI Platform). Generative AI Skills – Hands-on experience with large language models (LLMs) and understanding of advanced NLP techniques, such as text generation, summarization, and sentiment analysis. – Knowledge of GAN architectures for synthetic data generation, image processing, and computer vision applications. – Experience with fine-tuning pretrained models and applying transfer learning techniques to improve generative model performance. – Familiarity with prompt engineering and model customization for specific applications (e.g., chatbots, content generation). – Understanding of evaluation metrics and methods for Generative AI models, ensuring models perform reliably and ethically in production. Data Science and Analytical Skills – Expertise in statistical analysis, hypothesis testing, and interpreting data to derive actionable insights. – Strong data visualization skills using tools like Matplotlib, Seaborn, or Tableau to communicate findings and model results to stakeholders. – Experience in A/B testing, experimentation, and analysis to validate model performance and impact. – Ability to define, measure, and monitor key performance indicators (KPIs) to assess model effectiveness and alignment with business goals. – Proven ability to work with big data frameworks like Apache Spark or Hadoop for large-scale data processing. Communication and Collaboration Skills – Strong communication skills, with the ability to explain complex AI concepts to non-technical stakeholders and collaborate across teams. – Experience in documenting data science processes, model architectures, and analytical findings in a clear and organized manner. – Proven ability to work collaboratively in cross-functional teams with engineers, product managers, and designers to align on project goals. – Strong presentation skills for delivering data-driven insights and Generative AI use cases to business leaders and decision-makers. Additional Qualifications – Familiarity with data privacy and ethical considerations in AI, including bias mitigation, fairness, and compliance with industry regulations. – Experience in a specific industry like Telecommunications is a plus. – Demonstrated commitment to continuous learning, staying updated on the latest AI advancements and generative models. – Knowledge of MLOps and model monitoring tools (e.g., MLflow, Kubeflow) to ensure model reliability in production. Education: Bachelor’s or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field. #J-18808-Ljbffr