Description

SUMMARY:

Elligo’s Data Science team is a core group of highly skilled individuals focused on leveraging Elligo’s various data sources to drive core aspects of the company’s business. The Data Scientist plays an integral role as part of the Data Sciences team. Primary responsibilities include data modelling, data engineering, and analysis, along with additional expectations to develop scalable toolkits/methods to leverage Elligo’s data to support the business and its customers. Secondary responsibilities include designing and executing EMR-data queries and contributing to reporting projects.

Essential Duties

Analyze and develop search strategies and models for mining large data sets
Lead development of data tools and products incorporating technologies such as ML and AI
Develop novel methodologies for data analysis/processing to leverage Elligo’s datasets
Design, lead and execute on running queries against EHR data to support the business. Includes reviewing protocol inclusion/exclusion criteria, designing appropriate queries, executing searches, performing data cleaning, data analytics
Providing data product deliverables to teams for various business needs including feasibility studies, patient identification, business development inquiries, and exploratory work
Serve as resources to sites and internal teams for the purposes of ensuring data initiatives are achieving desired results

Qualifications

Ability to act and operate independently with minimal daily direction from manager to accomplish objectives
Strong data-science technical skills including proficiency in independently developing tools model building, training, tuning and deployment
Advanced proficiency with data-science programming in Python, including data manipulation (Pandas, numpy, scipy, etc.), ML/AI (tensorflow, pytorch, sklearn, etc.), visualization (matplotlib, plotly, seaborn, etc.), databases (SQL), and AWS-based ops
Ability to author peer-reviewed publications and scientific conference presentations to disseminate results of Data Science team’s efforts.
Outstanding written and verbal communication skills, especially the ability to effectively communicate technical details to individuals with a non-technical background
Excellent interpersonal skills and aptitude to collaborate effectively across various functional groups and different levels of employees.
Ability to work in a dynamic work environment with variable and competing demands.
Proactive and timely follow-up skills: the ability to organize applicable department timelines and follow up with internal and external stakeholder needs as needed.
Strong organizational skills: ability to accomplish multiple tasks within the agreed-upon timeframes through effective prioritization of duties and functions in a fast-paced environment.
Proven track record of building and maintaining solid relationships with both internal and external stakeholders.
Self-motivated; able to work independently to complete tasks respond to department requests and collaborate with others to utilize their resources and knowledge to identify quality solutions.

Education And Experience

MS/PhD in Data Science or a related computational field
5+ years of experience
Familiarity with healthcare data (EMR/EHR, claims, etc.) and healthcare operations (billing, coding, etc.)
Demonstrated experience working with large healthcare related datasets (EMR/HER, imaging, omics data)
Additional experience with advanced data platforms (e.g., Snowflake, Databricks, or Redshift) and ML-ops is desired

Environment

This is remote position based on the location of the incumbent’s home. This role routinely uses standard office equipment such as computers, printers, copiers, and phones.

Less than 10% will be required to support the position’s responsibilities.

Physical Demands

The physical requirements described here are representative of those that must be met by an employee to successfully perform the functions of the job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this job, the employee may:

work at a desk using a computer for prolonged periods,
regularly communicate via e-mail, telephone, chat, webcam (remote sessions such as MS Teams or Zoom), and exchange accurate and timely information,
frequently sit/stand/walk, grasp lightly/fine manipulation of objects,
occasionally reach/work above shoulders, twist/bend/stoop/squat, grasp forcefully, lift/carry/push/pull objects that weigh up to 20 pounds.

Additional

Elligo Health Research is a dynamic organization in a rapidly changing industry. Accordingly, the responsibilities associated with this job may change from time to time in accordance with business needs. More specifically, the incumbent may be required to perform additional and/or different responsibilities from those set forth above.

The above declarations are not intended to be an all-inclusive list of the duties and responsibilities of the job described, nor are they intended to be such a listing of the skills and abilities required to do the job. Rather, they are designed only to describe the general nature of the job.

The incumbent must be flexible as there may be workweeks that require more than 40 hours to ensure the position’s expectations and responsibilities are met.

Elligo Health Research is committed to a policy of equal employment and will not discriminate against an applicant or associate based on his or her age, sex, sexual orientation, gender identity, race, color, creed, religion, national origin or ancestry, citizenship, marital status, familial status, physical or mental disability, handicap, military or veteran status, genetic information, pregnancy or any other category protected under federal, state or local law, regulation or ordinance.

Requirements

MS/PhD in Data Science or a related computational field

5+ years of experience

Familiarity with healthcare data (EMR/EHR, claims, etc.) and healthcare operations (billing, coding, etc.)

Demonstrated experience working with large healthcare related datasets (EMR/HER, imaging, omics data)

Additional experience with advanced data platforms (e.g., Snowflake, Databricks, or Redshift) and ML-ops is desired