Data Scientist with Generative AI Experience

2 weeks ago

Atlanta, United States Highbrow LLC Full time

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.

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