Summary
Join our dynamic team as a Full Stack Data Scientist and 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
- 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
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
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