Ancestry.com Operations Inc. seeks Senior Data Scientist in Draper, UT (Previous location Lehi, UT)

Job Duties: Define a vision for the use of AIML, LLMs, CV, NLP to extract value and data-driven insights from our billions of genealogical records such as census records, newspapers, city directories, family history books, birth, marriage and death records, etc. Engage in fast prototyping, and agile software development and deliver measurement-driven model improvements. Perform applied research implementing SOTA generative AI, NLP, LLM, CV solutions for NER, relation extraction, summarization, topic analysis, entity resolution, knowledge graphs, embeddingsbased information retrieval, story generation, AI driven chat, etc. Collaborate with ML Ops and Data Science Engineers to deploy datasets, truth sets, models, pipelines, training and inference code to cloud based model registry and optimize AIML and GenAI algorithms. Partner with subject matter experts to inject their in-depth knowledge into the model creation process. Effectively communicate research results to stakeholders and the research community through documentation, white papers, peer-reviewed publications, and presentations. Help to recruit, inspire, and develop a high performing and creative Data Science AI team members. Telecommuting permitted.

Minimum Requirements: Master’s in Data Science, Computer Science, Statistics, Mathematics, Engineering or related discipline, or foreign equivalent, plus one year of experience in job offered or in a closely related position.

Special Skill Requirements: Experience must include one (1) year with each of the following: 1)Hands-on technical experience developing and deploying AIML models in production settings; 2) Leading efforts to design, implement, and deploy multiple data science projects end-to-end from idea generation, objectives formulation, to implementation, performance analysis and deliverables; 3) AIML methods including emerging Foundation Models and LLMs, NLP, CNN, RNN, transfer learning, attention mechanisms, large language models, transformers, generative models and embedding methods; 4) NLP techniques such as named entity extraction, document classification, summarization, topic modeling, relation extraction, sentiment analysis, dialogue systems; 5) Language models including variants of BERT, T5, GPT, Falcon, and LLaMA, as well as others such as Hugging face and OpenAI models; 6) AIML technologies including Python, Tensorflow, PyTorch, Keras, SciPy stack and Scikit-learn, NLTK, spaCy, pandas, and numpy.

EOE, including disability/vets.

Must be legally authorized to work in the U.S. without sponsorship.