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Emily Kramer Email & Phone Number

Data Scientist II at Unum
Location: Auburn, Maine, United States 4 work roles 2 schools
1 work email found @jpl.nasa.gov LinkedIn matched
✓ Verified Jul 2026 4 data sources Profile completeness 86%

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Work email e****@jpl.nasa.gov
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Current company
Role
Data Scientist II
Location
Auburn, Maine, United States
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Who is Emily Kramer? Overview

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Quick answer

Emily Kramer is listed as Data Scientist II at Unum, a with 9258 employees, based in Auburn, Maine, United States. AeroLeads shows a work email signal at jpl.nasa.gov and a matched LinkedIn profile for Emily Kramer.

Emily Kramer previously worked as Data Scientist at Unum and Scientist at Nasa Jet Propulsion Laboratory. Emily Kramer holds Doctor Of Philosophy (Phd), Physics And Planetary Science from University Of Central Florida.

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Email format at Unum

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{first}.{last}@jpl.nasa.gov
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Profile bio

About Emily Kramer

My position at Unum in Marketing Analytics gave me incredible insights in to how private industry handles data as compared to NASA. For my next position, I am looking to take on a more technical role with an emphasis on machine learning and pattern recognition, leveraging the experience I've gained at both Unum and JPL.As a Data Scientist at Unum, I developed and implemented Fuzzy Matching algorithm improvements which increased accurate company name matches by 10%, allowing more leads to be sent to sales representatives. I broadened my skill set to better align with the tech stack used in private industry, and quickly became versed in account based marketing, use of the Salesforce API, complex SQL queries, Azure Dev Ops, and many others.As a Staff Scientist at NASA’s Jet Propulsion Laboratory (JPL), my work focused on the collection and analysis of spatial image data to find low-strength signals and patterns, allowing broader trends to be detected. Using a combination of standard Python packages (e.g., numpy, scipy, matplotlib) and custom packages developed by our research team, I have written an extensive data analysis software suite in Python which used a novel fitting technique to characterize the data and find unexpected trends. The fitting software included binning of data, Gaussian fitting, outlier rejection via a clustering algorithm, and automatic comparison of the resultant data to physics-based dynamical models. I wrote the software in such a way that it could be run automatically on the entire data set as a script, generating visualizations of the results for each data point, and a collective presentation of the overall results.

Current workplace

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Unum
Unum
Data Scientist II
chattanooga, tennessee, united states
Website
Employees
9258
AeroLeads page
4 roles

Emily Kramer work experience

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Data Scientist Ii

Current

Portland, Maine Metropolitan Area

I will be working with the Advanced Analytics group in the Digital Transformation Organization, using emerging technologies to streamline business processes at Unum. I have already learned so much in the past 3 days, and I can't wait to see what is next!

Sep 2024 - Present

Data Scientist

Portland, Maine, United States

Key Skills: Account based marketing, Salesforce API, programming and process automation, complex SQL queries, Azure Dev Ops, Google Cloud, data visualization, machine learning· Key Contribution: Developed and implemented Fuzzy Matching algorithm improvements which increased ac- curate company name matches by 10%, allowing more leads to be sent to sales representatives

May 2023 - Sep 2024

Scientist

Independent research which included the development of analytical image modeling code written in Python to characterize the dust tails of comets. Use of data science methods to analyze image data. Conversion of the existing code from Python 2.x to 3.x, and updated to include object-oriented programming techniques, new Gaussian modeling methods, and data adaptive algorithms. Used standard Python software packages, including Numpy, Scipy, and Matplotlib. Used statistical techniques in Python, including K-S testing, to test hypotheses and predict outcomes by determining the fitness-of-use of the models to the data. Used standard data tools and techniques to structure the resulting large data set to aid in analysis and interpretation of the results.Participated in the development of a data pipeline to automatically process astronomical image data on a nightly basis, so that the data could be used to find potentially hazardous asteroids and comets. This project has involved database development, database management, quality assurance, and machine learning (selection of training data, vetting of algorithm).Co-lead of Comet Working Group, tasked with ensuring that comets could be detected and characterized by the NEO Surveyor spacecraft, as tasked by NASA's Planetary Defense Coordination Office. Development of novel comet modeling algorithms to generate synthetic images to predict the effectiveness of the NEO Surveyor mission. Used statistical techniques in Python, including K-S testing, to test hypotheses and predict outcomes by determining the fitness-of-use of the models to the data. Used standard data tools and techniques to structure the resulting large data set to aid in analysis and interpretation of the results.

Nov 2017 - Dec 2022

Postdoctoral Research Fellow

Pasadena, Ca

Developed computer code in Python to analyze infrared comet image data. Designing and developing of data analytics code to build models of comet tails to compare to actual data in a semi-automated manner, allowing data to be analyzed faster. Used standard Python analytical tools and data visualization tools including Numpy, Scipy, and Matplotlib. Developed algorithms and code to predict what the comet tails would look like given a variety of characteristics, then test that hypothesis by comparing to actual image data. Led the writing, and publication of, scientific papers in peer-reviewed journals.Participated in, and frequently led, tri-weekly quality assurance of infrared imaging data for the detection and characterization of asteroids and comets. Submitted results to the Minor Planet Center for further vetting and confirmation, leading to the discovery of hundreds of new asteroids and comets.Used numerous ground-based telescopes in a wide variety of locations to successfully collect astronomical data which was subsequently used in the publication of peer-reviewed scientific papers. Successfully completing an astronomical observing run requires a number of skills, including flexibility, stamina, persistence, identifying problematic issues, problem solving, data management, and the ability to incorporate changing conditions in to a plan on the fly.

Oct 2014 - Oct 2017
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Colleagues at Unum

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2 education records

Emily Kramer education

FAQ

Frequently asked questions about Emily Kramer

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What company does Emily Kramer work for?

Emily Kramer works for Unum.

What is Emily Kramer's role at Unum?

Emily Kramer is listed as Data Scientist II at Unum.

What is Emily Kramer's email address?

AeroLeads has found 1 work email signal at @jpl.nasa.gov for Emily Kramer at Unum.

Where is Emily Kramer based?

Emily Kramer is based in Auburn, Maine, United States while working with Unum.

What companies has Emily Kramer worked for?

Emily Kramer has worked for Unum and Nasa Jet Propulsion Laboratory.

Who are Emily Kramer's colleagues at Unum?

Emily Kramer's colleagues at Unum include Jp Buckley, Emily Berry, Katharine Rolph, Crc, Oscar Castro, and Kimberly Hause.

How can I contact Emily Kramer?

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What schools did Emily Kramer attend?

Emily Kramer holds Doctor Of Philosophy (Phd), Physics And Planetary Science from University Of Central Florida.

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