When you join Ancestry, you join a human-centered company where every person’s story is important. We believe that by discovering the struggles and triumphs of our past, we can foster deeper bonds and more meaningful connections among families and communities. Our talented team of scientists, engineers, genealogists, historians, and storytellers is dedicated to empowering customers around the world from all backgrounds on their journeys of personal discovery.
With more than 24 billion digitized global historical records, 100 million family trees, and 16+ million people in our growing AncestryDNA database, Ancestry helps customers discover their family story and gain actionable insights about their health and wellness. Passionate about dedicating your work to enriching people’s lives? You belong at Ancestry.
We are growing our Data Science team and looking for a Data Scientist to join our global Data Science & Machine Learning Team. You’ll have the opportunity to work alongside a high functioning group tackling Ancestry’s toughest and most exciting data science challenges, and with unique text data spanning decades across a variety of media channels. This position has the potential to be remote out of the following location: Texas, Utah, California and Colorado.
Use data science to drive product innovation, customer success, content creation across our Family History business.
Champion a data-driven culture and push long-term business value creation through development of best-in-class Data Science capabilities.
Leverage Natural Language Processing and Computer Vision to build handwriting recognition models that are able to extract information from our billions of genealogical and census records.
Who you are...
Bachelor’s Degree in Computer Science, Statistics, or other data-related field coupled with 4 + years industry experience in machine learning and statistical modeling OR
Master’s Degree in Computer Science, Statistics, or other data-related field coupled with 2+ years industry experience in machine learning and statistical modeling OR
PhD in Computer Science, Statistics, or other data-related field coupled with some industry experience in machine learning and statistical modeling
Experience with machine learning techniques ie: entity extraction, document classification, topic modeling, computer vision methods, object detection, image classification, and handwriting recognition
Proven track record of completing multiple data science projects end-to-end; from idea generation, objectives formulation, to implementation and deliverables
Strong proficiency in Python, experience with Java, SQL, and multi-threaded programming preferred
Experience building deep learning models using tools like TensorFlow and Pytorch
Strong preference for experience building ML models for handwriting recognition
Ancestry is an Equal Opportunity Employer that makes employment decisions without regard to race, color, religious creed, national origin, ancestry, sex, pregnancy, sexual orientation, gender, gender identity, gender expression, age, mental or physical disability, medical condition, military or veteran status, citizenship, marital status, genetic information, or any other characteristic protected by applicable law. In addition, Ancestry will provide reasonable accommodations for qualified individuals withdisabilities.
All job offers are contingent on a background check screen that complies with applicable law. For San Francisco office candidates, pursuant to the San Francisco Fair Chance Ordinance, Ancestry will consider for employment qualified applicants with arrest and conviction records.
Ancestry is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at Ancestry via-email, the Internet or in any form and/or method without a valid written search agreement in place for this position will be deemed the sole property of Ancestry. No fee will be paid in the event the candidate is hired by Ancestry as a result of the referral or through other means