Remote AI-Driven Data Architect & Scientist

OpenKrill; United States; Remote; USD 180,000 - 190,000; Full time

Benefits offered by this job

401(k) Retirement Plan

Professional development & training

Job summary

DLH Corporation is seeking a senior data science and data engineering professional to drive strategy for a custom data platform and collaborate with scientists and trainees in a federal healthcare enterprise environment.

The role involves designing and testing solutions across server/storage, network, and application development, communicating findings to diverse stakeholders, and building tools to optimize data collection, validation, and analysis.

Qualifications

• Bachelor’s degree in data science, bioinformatics, or related field or equivalent combination of education and experience and appropriate technical certifications.
• At least twelve (12) years of information technology experience and 4 years leading or performing data engineering or related functions.
• Experience manipulating big data and solving complex problems.

Responsibilities

• Lead data science strategy in support of custom data platform.
• Collaborate with scientists and trainees.
• Support a federal healthcare enterprise environment by collaborating with IT operational service areas (server/storage, network, application development) in design, development, and testing of solutions.
• Communicate findings, recommendations, and solutions to technical and non-technical stakeholders.
• Design tools for optimizing data collection, validation, and analysis.

Skills

Python

R

MATLAB

Big data

Agile

Communication

Education

Bachelor’s degree in data science or related field

Job description

DLH Corporation is seeking a senior data science and data engineering professional to drive strategy for a custom data platform and collaborate with scientists and trainees in a federal healthcare enterprise environment.

The role involves designing and testing solutions across server/storage, network, and application development, communicating findings to diverse stakeholders, and building tools to optimize data collection, validation, and analysis.