188 applicants

Company

QinetiQ · 7 hours ago

Data Scientist

Washington, DC

Full-time

Remote

Senior Level

5+ years exp

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Responsibilities

Develop and implement sophisticated data models to analyze complex datasets, identify patterns, and extract actionable insights.

Apply advanced statistical and machine learning techniques to solve business problems, predict trends, and optimize performance.

Collaborate with stakeholders to understand data requirements and translate them into effective modeling strategies.

Develop and implement advanced data models, algorithms, and statistical models to solve complex business problems.

Apply machine learning techniques, such as regression, clustering, classification, and natural language processing, to extract insights from large and diverse datasets.

Utilize exploratory data analysis to identify patterns, correlations, and trends in data.

Design, develop, and evaluate predictive models to support forecasting, risk assessment, and decision optimization.

Utilize machine learning algorithms and techniques to develop models for classification, regression, clustering, and anomaly detection.

Leverage knowledge of a variety of statistical and machine learning techniques and methods to define and develop programming algorithms; train, evaluate, and deploy predictive analytics models that directly inform mission decisions.

Conduct model performance evaluation, fine-tuning, and optimization to ensure accurate and reliable predictions.

Clean, preprocess, and transform raw data to ensure data quality and integrity.

Develop and apply data preprocessing techniques, including feature engineering, dimensionality reduction, and outlier detection.

Collaborate with data engineering teams to optimize data pipelines for efficient data ingestion and preprocessing.

Execute projects including those intended to identify patterns and/or anomalies in large datasets; perform automated text/data classification and categorization as well as entity recognition, resolution and extraction; and named entity matching.

Create compelling visualizations and reports to effectively communicate complex analytical findings and insights to both technical and non-technical stakeholders.

Develop interactive dashboards and data visualizations using tools such as Tableau, Power BI, or similar platforms.

Transform complex analysis results into clear, concise narratives that drive understanding and action.

Explore and analyze large and complex datasets to identify relevant features and variables for modeling and analysis.

Collaborate with data engineering teams to access and integrate data from various sources, ensuring data quality and consistency.

Conduct feature engineering, data transformation, and data preprocessing to optimize model performance and accuracy.

Collaborate with engineering teams to deploy models into production systems, ensuring scalability, reliability, and performance.

Implement monitoring and evaluation frameworks to track model performance over time, identifying and addressing potential issues.

Continuously improve and refine models based on feedback, new data, and evolving business requirements.

Collaborate with cross-functional teams, including data engineers, business stakeholders, and software developers, to drive data science initiatives and ensure successful project outcomes.

Provide input on platform architecture and development tools.

Utilize technical knowledge outside of data science to assist in application development, data pipelines, and AWS cloud infrastructure.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data ModelingMachine LearningPredictive AnalyticsStatistical AnalysisData Querying (SQL)PythonTensorFlowNLPRSASMatlabData Visualization TableauData Visualization Power BIAWSDatabricksPower PlatformOCRDocument UnderstandingLLMsGenAICross-functional Collaboration

Required

Bachelor's or Master's degree in a quantitative field, such as Data Science, Computer Science, Statistics, or a related discipline.

Proven experience (5+ years) as a Data Scientist, with a focus on data modeling, predictive analytics, and machine learning.

Strong expertise in data modeling techniques, statistical analysis, and machine learning algorithms.

Solid ability with data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience.

Proficiency in TensorFlow (or PyTorch), Numpy, Pandas, and other standard Data Science/ML libraries.

Strong problem-solving and analytical thinking abilities, with the ability to work with complex and unstructured datasets.