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SO
System One
Mid-Level Data Scientist
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Based on Virginia data
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What they do
A Data Scientist utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management.
$101,474 / year median in Virginia
+18% projected growth
Job Description
Job Title:
Mid-Level Data Scientist Location:
Vienna, VA Type:
Contract Compensation:
Hybrid - onsite and remote Responsibilities- Collaborate with senior data scientists and leaders to design and implement predictive models and custom solutions that enhance our digital offerings.
- Partner with business units to gather requirements, understand customer needs, and develop data science solutions that address specific business challenges.
- Write efficient code in Python and SQL to manipulate and analyze data.
- Design, develop, and evaluate predictive models and algorithms with moderate to high complexity.
- Utilize traditional and machine learning techniques and tools to build a variety of models, including but not limited to logistic regression, XGBoost, neural networks, NLP, k-means clustering, ARIMA, and prophet forecasting.
- Analyze and interpret results with some complexity.
- Exercise limited judgment and discretion within defined procedures and practices.
- Develop and code modeling programs, algorithms, and automated processes.
- Use modeling and trend analysis to analyze data.
- Collaborate with team members and participate in team projects and initiatives.
- Utilize effective written and verbal communication to document and present findings. Requirements
- 3-7 years of experience (mid-level) in data science, statistics, and data analytics.
- Ability to work with moderate to minimal supervision.
- Strong programming abilities in SQL, Python, PySpark, R, or similar languages in data exploration, data preparation, modeling, prediction, simulation, and statistical analysis.
- Experience with machine learning techniques and tools to build a variety of models, including logistic regression, XGBoost, neural networks, NLP, and clustering.
- Ability to use data and cloud environments such as Azure, Databricks, AWS, or Hadoop.
- Familiarity with project management tools such as Azure Dev Ops (ADO), or JIRA is a plus.
- Technical writing skills.
- Strong communication and data storytelling presentation skills of technical material.
- Ability to collaborate and build relationships.