Lead Data Scientist - GenAI

at  Tiger Analytics

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.
As a Data Scientist, you will apply strong expertise in AI through the use of machine learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

REQUIREMENTS

• 8+ years of experience working as a GenAI Data Science.
• Experience with Python from a functional programming paradigm, able to manage dependencies and virtual environments, along with version control in git
• Experience with sequential algorithms (e.g., LSTM, RNN, transformer, etc.)
• Experience with Bedrock, JumpStart, HuggingFace
• Experience evaluating ethical implications of AI and controlling for them (e.g., red-teaming)
• Expertise in supervised learning and unsupervised learning along with experience in deep learning and transfer learning
• Experience in generative algorithms (e.g., GAN, VAE, etc.) as well as pre-trained models (e.g., LLaMa, SAM, etc.)
• Experience developing models from inception to deployment

• Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools.
• Experiment, evaluate, and create generative AI products for a variety of tasks, such as extracting data, summarizing documents, and other generative model applications.
• Use fine tuning and advanced knowledge retrieval methods to improve the performance of generative AI models on specific tasks
• Evaluate the performance of models and make necessary improvements
• Collaborate with other scientists, data engineers, machine learning operations engineers, prompt engineers, and product owners to develop generative AI products
• Engineer features by using your business acumen to find new ways to combine disparate internal and external data sources.
• Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards.
• Collaborate, coach, and learn with a growing team of experienced Data Scientists.
• Stay connected with external sources of ideas through conferences and community engagements