Full Stack Data Scientist

rockITdata

Full Stack Data Scientist at rockITdata leveraging advanced analytics to drive impactful business outcomes. Collaborating with teams to build scalable data-driven solutions in the healthcare industry.

Posted 7/11/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying machine learning models, data preprocessing, and exploratory data analysis. Proficient in utilizing programming languages and data visualization tools to derive insights and build scalable data solutions.

Highest-signal resume keywords

Data PreprocessingExploratory Data AnalysisMachine Learning AlgorithmsPython ProgrammingData Visualization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data PreprocessingExploratory Data AnalysisFeature EngineeringMachine Learning AlgorithmsStatistical ModelingPython ProgrammingR ProgrammingSQLTensorFlowPyTorch

Tools & Technologies

QlikTableauPower BIAWSAzureGCP

Industry Keywords

Data ScienceData PipelinesPredictive ModelsCloud EnvironmentsSoftware Engineering Principles

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonPyTorchScikit-LearnSQLTableauTensorflow

About the role

Key responsibilities & impact

Develop robust data pipelines for acquiring, cleaning, and preprocessing large-scale datasets from various sources.
Conduct comprehensive exploratory data analysis to uncover patterns, trends, and insights within the data.
Design, develop, and deploy predictive models using advanced machine learning algorithms and techniques.
Build scalable and efficient software solutions for deploying machine learning models into production environments.
Establish monitoring mechanisms to track the performance of deployed models and identify opportunities for improvement.
Collaborate closely with cross-functional teams including data engineers, software developers, and business stakeholders.

Requirements

What you’ll need

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
Proven experience in data preprocessing, exploratory data analysis, and feature engineering.
Expert-level skills in data visualization platforms (e.g. Qlik, Tableau, Power BI)
Proficiency in programming languages such as Python, R, and SQL for data manipulation and analysis.
Strong understanding of machine learning algorithms and statistical modeling techniques.
Hands-on experience with machine learning libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc.
Experience in developing and deploying end-to-end data science solutions in cloud environments (e.g., AWS, Azure, GCP).
Solid understanding of software engineering principles and best practices for building scalable and maintainable code.

Benefits

Comp & perks

Health insurance
Flexible work arrangements
Paid time off
Professional development opportunities