Qualifications:
We are seeking an experienced Data Scientist to join our team, focusing on the development and deployment of Generative AI (GenAI) solutions in a commercial business setting. This role involves working with advanced technologies, including vector databases, Retrieval-Augmented Generation (RAG) approaches, and building end-to-end AI pipelines to deliver actionable insights and solutions to business challenges.
No additional medical exams are required except for drug screening.
EDUCATION:
- Master's or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field.
EXPERIENCE/SKILLS:
- Proven experience in NLP and in developing and deploying Generative AI models in business settings, along with expertise in LLM prompt engineering and familiarity with LLM-based workflows and architectures.
- Proficient in handling natural language data and developing text/number-based products using a combination of traditional and cutting-edge NLP techniques (such as text mining, word embeddings, and transformer-based models).
- Strong programming skills in Python, R, or similar languages.
- Experience with data manipulation and analysis using tools like SQL, Pandas, and NumPy.
- Solid understanding of statistical analysis and data visualization techniques, with experience in effective visualization tools such as Power BI and Tableau, along with a keen eye for detail in the visual communication of findings.
- Experience with Databricks, MLflow, Azure, endpoint deployment, LangChain, LlamaIndex, Hugging Face or similar services.
- Knowledge of encoder-decoder architectures, diffusion models, and other relevant techniques, is a plus.
- Excellent problem-solving skills and the ability to work independently and collaboratively.
- Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
Preferred Qualifications:
- Experience with natural language processing (NLP), computer vision, foundation model fine-tuning, and deep learning applications.
- Familiarity with cloud platforms such as Azure.
- Experience in project management and leading data science initiatives.
Responsibilities:
Responsibilities:
- Model Development: Design, develop, and optimize RAG (Retrieval-Augmented Generation) models, knowledge graph to facilitate effective information retrieval and generation directed to solve complex business problems and enhance decision-making process.
- Vector Database Management: Utilize vector databases and advanced indexing techniques to efficiently store and retrieve relevant information for conversational contexts.
- LLM Fine-Tuning: Fine-tune and optimize large language models (LLMs)
- NLP Techniques: Implement and experiment with cutting-edge NLP (Natural Language Processing) and other similar techniques to enhance the capabilities and performance of our AI products.
- Collaboration: Collaborate with cross-functional teams such as business and with platform and software engineers to identify opportunities for integrating Generative AI models into production systems, ensuring scalability, reliability, and performance.
- Build and deliver compelling data visualizations, websites, apps, and outputs to effectively communicate findings to technical collaborators, non-technical audiences, and business leaders.
- Communicate findings and recommendations to stakeholders through clear and concise reports and presentations.
- Stay up-to-date with the latest advancements in Generative AI and data science technologies by engaging with the broader data science community to remain updated about methodologies, software advancements, GenAI, and the development and availability of data.
| Start Time: | 8:00 AM |
| End Time: | 5:00 PM |
