Operational Data Scientist

IBM

Quick summary

Work type: On-site
Location: Herndon, VA
Posted: 11 days ago
Nearby: 99+ roles within 25 mi

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Similar $162k

$97k most similar roles pay here $233k

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Based on 240 similar postings.

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About IBM

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 Herndon, VA. This role involves collaborating closely with cross-functional teams to develop and implement advanced analytics solutions that enhance operational efficiency and decision-making processes. Day-to-day responsibilities include analyzing complex datasets, building predictive models, 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 cloud platforms like AWS or Azure is highly desirable. This position plays a crucial role in addressing critical business challenges within the defense sector, requiring strong problem-solving skills and an ability to work under tight deadlines.

Skills

Python SQL Pandas NumPy Scikit-learn TensorFlow Keras AWS Google Cloud Platform Azure Docker Kubernetes CI/CD Git Jupyter Notebook PostgreSQL MongoDB Snowflake Tableau PowerBI

What you'll do

Analyze complex operational data to identify trends and patterns.
Develop predictive models to forecast future operational outcomes.
Implement machine learning algorithms to optimize operational processes.
Create visualizations and dashboards for stakeholders to monitor performance.
Maintain and update databases with accurate, real-time operational data.

What we're looking for

Must hold TS/SCI clearance with polygraph.
Requires strong background in data science and analytics.
Proficient in Python/R for statistical analysis and modeling.
Experience with big data technologies like Hadoop or Spark.
Ability to extract insights from complex datasets and communicate findings.
Knowledge of machine learning algorithms and predictive modeling techniques.
Strong problem-solving skills and attention to detail.

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