Data Scientist (Generative AI)

Data Scientist (Generative AI)

Work location: Atlanta, GA

Duration: 12 Months

Need local candidates only.

Bachelor s degree in Data Science, Computer Science, Statistics, or a related field. A Bachelor's or Master s degree is preferred.

5+ 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, Google Cloud Platform, 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 pre-trained 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.