Data Scientist (Generative AI)

Job Description:

• 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.
• 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, and BERT) with hands-on experience in training, fine-tuning, and deploying these models.
• Proficient in data wrangling and preprocessing with tools like Pandas, and 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).
• 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.

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.