Data Scientist Generative AI

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)

• 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 Tensor Flow, 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, Num Py, 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 Sage Maker, 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.