Full Stack Data Scientist

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.

Key Responsibilities
- Data Collection and Preprocessing:
- 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.

- Exploratory Data Analysis and Visualization:
- 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.

- Machine Learning Model Development:
- Design, develop, and deploy predictive models using advanced machine learning algorithms and techniques.

- Optimize model performance through feature engineering, hyperparameter tuning, and model selection.

- Software Development and Integration:
- 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.

- Performance Monitoring and Maintenance:
- 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.

- Collaboration and Cross-functional Communication:
- 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.

Required Qualifications
- 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.

Preferred Qualifications
- 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.

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