Data Scientist (Ai/Ml And Genai)

Skill: Data Scientist with Generative AI Expertise

Role & Responsibilities:

• Design, develop, and implement advanced AI solutions to solve complex business problems across various domains.

• Collaborate with engineers, researchers, and product managers to understand business needs and translate them into technical specifications for AI models.

• Gather, clean, and prepare data for training and evaluating sophisticated AI models, ensuring data quality and ethical considerations.

• Explore and implement state-of-the-art AI techniques, including deep learning, natural language processing, and computer vision, tailored to specific needs.

• Evaluate and compare different AI model architectures and hyperparameters to optimize performance, address potential biases, and ensure responsible development.

• Develop monitoring and evaluation frameworks to track AI model performance and ensure alignment with business goals.

• Communicate complex AI concepts and findings to technical and non-technical audiences through data visualization, storytelling, and presentations.

Skills

Technical:

• Programming languages: Python (proficient) with major ML libraries.

• Experience with opensource Gen AI LLMs e.g., Llama and Dolly.

• Machine learning, NLP & deep learning: Strong understanding of supervised and unsupervised learning, neural networks, transformers.

• Generative AI techniques: Experience with GANs, text-to-image generation, text generation models.

• Data wrangling & manipulation: SQL, data cleaning, feature engineering.

• Hyperscalers: AWS, Azure, or GCP experience a plus

Non-technical:

• Problem-solving & critical thinking: Ability to identify and solve complex problems with data-driven solutions.

• Communication & collaboration: Effectively communicate technical concepts to diverse audiences, work with geographically distributed teams.

• Innovation & creativity.

• Attention to detail & accuracy.

• Self-motivation & continuous learning.