Ramsey Jones
Data AnalystAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Scientist | Generative Models | Geometric Deep Learning | Computer Vision
A startup veteran with wide experience in 2D and 3D computer vision, deep learning, and generative models. For better or worse I never could shake my childhood curiosity. It is the driving force of my career and a disruptive force to my apartment with every new hobby claiming its space. As a seasoned top-down and continuous learner, I am at home in what I don't know. I am always eager for the next challenge, ready to adapt and to seize the opportunity to wear as many different hats as possible. Holding to the always-growing collection of hobbies and causes close to my heart, I am always in search of how to connect the machine learning skills and career I've built to what I care about. From agriculture to equitable urbanism, sustainability, medicine, and to education, the support AI can offer the areas important to me is what most excites me.
University of Minnesota
Master of Science (M.S.), Physics, Mathematics Minor
January 1, 2013 – January 1, 2015
University of Washington
Bachelor of Science (B.S.), Physics, Astronomy, Mathematics Minor
January 1, 2010 – January 1, 2013
Solventum
Senior Machine Learning Scientist
May 1, 2024 – Present
SmileDirectClub
Senior Machine Learning Scientist
July 1, 2021 – December 1, 2023
Remote
Imbellus
Senior AI Research Scientist
February 1, 2019 – November 1, 2020
Imbellus
Senior AI/ML Engineer
March 1, 2017 – February 1, 2019
Jivry, Inc
Chief Scientist, Co-founder
July 1, 2015 – August 1, 2016
Seattle, New York City
University of Minnesota
Teaching Assistant
August 1, 2013 – May 1, 2015
Greater Minneapolis-St. Paul Area
Theoretical Cosmology
February 1, 2014 – September 1, 2014
Performing research in theories of the very early universe. Developing a model of cosmological inflation to account for anomalies in the data from the Planck satellite's observations of the cosmic microwave background.
Machine Learning in High Energy Physics
June 1, 2012 – January 1, 2013
Testing a new machine learning algorithm for parameter searches in cosmology and high energy physics against standard MCMC methods.
Astronomical Image Analysis
March 1, 2012 – June 1, 2012
Observing and performing image analysis on the transit of an extra-solar planet. Using Python and IRAF to process the images to construct a light curve showing the drop in luminosity as the planet passes in front of its host star.
Computational Astrophysics
January 1, 2011 – June 1, 2012
Performing research in computational astrophysics. Using a flux anomaly between images of a gravitationally lensed quasar to probe substructure of the lensing galaxies. Developing statistically significant alterations to the model of the lens structure leading to publication in the Astrophysical Journal.
Cultural Fit Analysis
The candidate has a strong background in academic research and startup environments, transitioning into senior ML scientist roles. The projects are highly technical and research-oriented, aligning with roles requiring deep analytical and problem-solving skills. However, the target role is 'Data Analyst', which might be a step down from their 'Senior Machine Learning Scientist' and 'Senior AI Research Scientist' roles. While the analytical skills are strong, the direct alignment with typical data analyst responsibilities (e.g., dashboarding, reporting, business intelligence) is not explicitly demonstrated. The breadth of skills listed (Machine Learning, SQL, Python) is relevant, but the depth in specific data analysis tools or methodologies beyond ML is not clear.
Soft Skills & Operational Fit
The candidate's experience as a co-founder and senior scientist suggests strong problem-solving, leadership, and independent research capabilities. The descriptions of patented algorithms and publications indicate a drive for innovation and a results-oriented approach. However, specific details on collaboration, project management, or communication within a team context are not explicitly provided in the operational descriptions.