Full Stack Data Scientist

rockITdata•Arlington, VA

13d•Remote

About The Position

Driven by Innovation and built on Trust, rockITdata is a unique SDVOSB services company that partners with leading commercial healthcare/life sciences organizations on cutting edge innovations - think AI, automation and data transformation. We then bring those commercially tested solutions to government entities to deliver predictable, measurable impact for the American taxpayer and consumer. We are seeking a highly skilled and innovative Full Stack Data Scientist to join our dynamic team. The ideal candidate will possess a strong background in both data science and software engineering, with a focus on developing end-to-end data-driven solutions. This role offers an exciting opportunity to leverage advanced analytics and cutting-edge technologies to drive impactful business outcomes. This is a Remote position.

Requirements

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.

Nice To Haves

Experience building solutions for Commercial clients in Pharma, Biotech, CPG, Retail or Manufacturing industries.
Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.
Knowledge of DevOps practices for continuous integration and deployment (CI/CD).
Experience with distributed computing frameworks for parallel processing (e.g., Dask, Ray).
Strong problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment.

Responsibilities

Develop robust data pipelines for acquiring, cleaning, and preprocessing large-scale datasets from various sources.
Implement strategies for data quality assessment and assurance to ensure reliable analysis outcomes.
Conduct comprehensive exploratory data analysis to uncover patterns, trends, and insights within the data.
Create interactive visualizations and dashboards to effectively communicate findings to stakeholders.
Design, develop, and deploy predictive models using advanced machine learning algorithms and techniques.
Optimize model performance through feature engineering, hyperparameter tuning, and model selection.
Build scalable and efficient software solutions for deploying machine learning models into production environments.
Integrate data science workflows with existing systems and applications to enable seamless data-driven decision-making.
Establish monitoring mechanisms to track the performance of deployed models and identify opportunities for improvement.
Conduct regular maintenance activities to ensure the reliability, stability, and scalability of data science solutions.
Collaborate closely with cross-functional teams including data engineers, software developers, and business stakeholders.
Communicate technical concepts and findings effectively to both technical and non-technical audiences.