Data Scientist

  • Washington, DC
  • Posted 7 days ago | Updated 7 days ago

Overview

Hybrid
$75,000 - $90,000
Full Time
No Travel Required

Skills

data science
sas
python
r
data modeling
data mining

Job Details

Ignitec infuses industry standards and leading technology capabilities to solve complex problems and deliver value with increased quality and lower performance risks. Our solutions combine top technology personnel, the latest cutting-edge technology, and Agile approaches to bring innovative ideas to life. We do not seek to meet expectation, we continuously strive to exceed them.

We have received our MBE Certification from NMSDC as a certified Minority Small Business Enterprise. We take pride in the MBE certification and partner with organizations to meet their Minority (D&I) Small Business goals. We are also a certified Minority Business Enterprise by the USPAACC, which recently awarded Ignitec The FAST 50 Asian American Business Award in 2022. We are also DBE certified by the Virginia Department of SBSD.

Location: Washington D.C (80% remote, 20% on-site)

Qualifications & Education

  • Bachelor s degree (or equivalent) in statistics, applied mathematics, or related discipline.

Required Skills

  • 3+ years experience in data science related field
  • Proficiency with data mining, mathematics, and statistical analysis
  • Advanced experience in pattern recognition and predictive modeling
  • Experience with Excel, PowerPoint, Tableau, SQL, and programming languages (ex: Java/Python, SAS)
  • Ability to work effectively in a dynamic, research-oriented group that has several concurrent projects.

Job Duties

  • Serve as lead data strategist to identify and integrate new datasets that can be leveraged through our product capabilities and work closely with the engineering team in the development of data products.
  • Execute analytical experiments to help solve problems across various domains and industries.
  • Identify relevant data sources and sets to mine for client business needs and collect large structured and unstructured datasets and variables.
  • Devise and utilize algorithms and models to mine big-data stores; perform data and error analysis to improve models; clean and validate data for uniformity and accuracy.
  • Analyze data for trends and patterns and interpret data with clear objectives in mind.
  • Implement analytical models in production by collaborating with software developers and machine-learning engineers.
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