Command|Link is seeking a Data Scientist to design, build, and operationalize predictive models that drive business impact across their SaaS platform, tackling complex data challenges to create scalable, production-ready solutions.
Requirements
- 3+ years of professional experience as a Data Scientist or ML Engineer.
- Proven experience building and deploying machine learning models in production environments.
- Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow).
- Strong knowledge of model deployment frameworks and tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI, or equivalent).
- Hands-on experience with cloud platforms (AWS, GCP, or Azure) for ML workflows.
- Solid understanding of data structures, algorithms, and applied statistics.
- Experience with MLOps best practices (CI/CD pipelines for ML, monitoring, and governance).
Responsibilities
- Design, develop, and validate machine learning models for classification, regression, recommendation, NLP, or time-series use cases.
- Own the full ML lifecycle: data exploration, feature engineering, model selection, training, testing, deployment, and monitoring.
- Collaborate with data engineering teams to ensure data pipelines are optimized for modeling and production use.
- Deploy ML models into production environments, ensuring scalability, reliability, and low-latency performance.
- Monitor and maintain deployed models, performing re-training and tuning as needed to ensure continued accuracy and relevance.
- Work with product managers and stakeholders to translate business requirements into measurable ML solutions.
- Research and experiment with emerging ML algorithms, frameworks, and deployment strategies.
Other
- This is a 100% remote position
- Strong problem-solving skills and the ability to communicate complex ideas clearly to both technical and non-technical audiences.
- Room to grow at a high-growth company
- An environment that celebrates ideas and innovation
- Your work will have a tangible impact
