> For the complete documentation index, see [llms.txt](https://info.askmyfi.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://info.askmyfi.com/careers/lead-data-scientist.md). # Lead Data Scientist **Company background:** Myfi is a dynamic and innovative wealthtech company committed to empower people to take control of their financial outcomes by providing access to intelligent and unbiased financial advice. MyFi is an AI powered financial assistant that serves to break down the complexities around financial planning so that users can make better decisions. Through a conversational chatbot experience, MyFi makes the start of your financial journey seamless. We are passionate about pushing the boundaries of technology and delivering exceptional solutions to our users. Our goal is to provide better wealth outcomes for every individual through a conversational AI powered Co-pilot. Download our beta app [from here](https://askmyfi.onelink.me/4AA4/820w6lmy) **Our Culture:** * We’re a fast paced startup looking impact lives through technology and innovation * Ownership and self-motivation is key, we don’t believe in micro managing * We’re outcome and impact driven, something isn’t done until a user benefits from it **Our Values:** Go With You **GUT** * **G**row At the Edge: We are driven by personal growth. We get out of our comfort zones and keep egos aside to find our genius zones. With self-awareness and integrity we strive to be the best we can possibly be. No excuses. * **U**nderstanding through Listening and Speaking the Truth: We value transparency. We communicate with radical candour, authenticity and precision to create a shared understanding. We challenge, but once a decision is made, commit fully. * I Win for **T**eam Win: We believe in staying within our genius zones to succeed and we take full ownership of our work. We inspire each other with our energy and attitude. We fly in formation to win together. **Key responsibilities:** * Work closely with the design and product teams to help craft conversational experiences for our users * Ability to work independently to deliver features that the team design * You need to own outcomes without someone watching over you * Understand the data we have and identify how we could leverage it to create more personalised experiences for our users * Fine tune models with data specific to our use case * Use different RAG approaches to augment data that the LLM already has * Ability to be a leader and independent contributor (we’re a startup so be ready to do whatever it takes) * Setup new workflow, systems and tool from the ground up (you will have support, but we’re building things from scratch) **Requirements:** * Masters/Bachelor's degree in computer science, mathematics, statistics, engineering, or relevant field * 10+ years of overall work experience * 1-2 Experience working with LLMs and Generative AI * Hands-on experience in various LLM fine-tuning techniques (e.g. LORA), LLM inference frameworks (e.g. vLLM), advanced RAG pipelines * 5-6 years of machine learning/deep learning experience within frameworks such as TensorFlow and/or PyTorch * Experience using RAG base approaches * Understanding of financial concepts and investing would be a big plus but not required * Publications at reputable machine learning conference or journal To apply for this role, please email --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://info.askmyfi.com/careers/lead-data-scientist.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.