Operational Data Scientist

IBM

Quick summary

Work type: On-site
Location: Chantilly, VA
Posted: 12 days ago
Nearby: 99+ roles within 25 mi

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Similar $161k

$96k most similar roles pay here $228k

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IBM is a US-based global technology company providing hybrid cloud, AI, consulting, enterprise software, and IT infrastructure products and services.

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TL;DR · Operational Data Scientist

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We are seeking a mid-level Operational Data Scientist with TS/SCI clearance to join our dynamic team in Chantilly, Virginia. This role involves collaborating closely with cross-functional teams to develop and implement advanced data analytics solutions that enhance operational efficiency and decision-making processes. Day-to-day responsibilities include designing predictive models, conducting statistical analyses, and creating visualizations to communicate insights effectively. The ideal candidate will have expertise in Python or R for data manipulation and analysis, proficiency in SQL for database querying, and experience with machine learning frameworks such as scikit-learn or TensorFlow. Additionally, familiarity with big data technologies like Hadoop or Spark is highly desirable. This position plays a crucial role in addressing complex business challenges within the intelligence community, requiring strong problem-solving skills and an ability to work on high-stakes projects at scale.

Skills

Python SQL Pandas NumPy Scikit-learn TensorFlow Keras AWS Azure Git Jupyter Notebook CI/CD Docker Kubernetes Prometheus Grafana PostgreSQL MongoDB

What you'll do

Analyze complex operational data to identify trends and insights.
Develop predictive models to forecast future operational scenarios.
Implement machine learning algorithms to automate data processing tasks.
Create visualizations to communicate findings to stakeholders effectively.
Maintain and update databases to ensure accurate and timely analysis.

What we're looking for

Must hold TS/SCI clearance with polygraph.
Requires experience in data analysis and operational research.
Proficient in statistical software and programming languages like Python/R.
Strong background in machine learning and predictive analytics needed.
Experience with big data platforms such as Hadoop or Spark is essential.

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