Published: Mon, 18 Nov 2024 16:50:28 GMT
Position: Data Scientist
Company: CoLab Software
Location: [Insert location here]
Overview: CoLab Software is seeking a talented and driven Data Scientist to join our team. At CoLab, we specialize in helping engineering teams accelerate their product development process through our innovative Design Engagement System (DES). Our clients include some of the biggest names in various industries, such as Ford, Johnson Controls, Komatsu, and Polaris. As a Data Scientist at CoLab, you will have the opportunity to work on cutting-edge projects in a collaborative and supportive environment, where your unique skills and perspectives are valued. We offer competitive compensation, comprehensive benefits, and a strong commitment to work-life balance. We encourage individuals from historically marginalized groups to apply, even if they do not meet 100% of the qualifications, as we value potential and diversity in our team.
Responsibilities:
• Design, implement, and deploy machine learning models to drive insights and automate business processes.
• Develop and optimize features for model training using large, complex datasets.
• Lead hypothesis-driven analysis and A/B testing to inform model and product development.
• Communicate findings through compelling visualizations and presentations, translating data into actionable insights for stakeholders.
• Oversee end-to-end model deployment using MLOps best practices, ensuring models are robust, reproducible, and scalable.
• Work with Platform Engineering to develop and maintain automated data pipelines to support continuous integration and deployment (CI/CD) for machine learning workflows.
• Set up monitoring and alerting for model drift, accuracy, and performance to maintain high-quality predictions in production.
• Work with engineering and platform teams to optimize cloud infrastructure, model serving, and resource allocation.
• Partner with product managers, engineers, and other data scientists to integrate ML solutions into the product and deliver on key business objectives.
• Ensure compliance with data privacy and security regulations in all aspects of data processing and model deployment.
• Advocate for best practices and contribute to the development of reusable frameworks and processes that accelerate the ML lifecycle.
Qualifications:
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
• 3+ years of experience in data science and machine learning, preferably in a SaaS environment.
• Strong programming skills in Python (experience with libraries like Pandas, Scikit-Learn, TensorFlow, PyTorch).
• Proficient in SQL and experience with data querying and transformation.
• Experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (e.g., MLflow, Kubeflow, Docker).
• Familiarity with CI/CD pipelines, version control (Git), and automated testing.
• Excellent problem-solving abilities, attention to detail, and the ability to work autonomously in a fast-paced environment.
• Strong communication skills with the ability to explain complex concepts to both technical and non-technical audiences.
• Willingness to contribute ideas and improve processes.
• Experience working on SaaS, large-scale distributed systems would be considered an asset.
• Consistent track record of building and maintaining highly scalable products would be considered an asset.
Success Measured By:
• Model Accuracy and Impact: Achieving target accuracy and driving measurable business impact.
• Deployment Efficiency: Speed and reliability in moving models to production, with minimal downtime.
• Monitoring and Maintenance: Effective model monitoring with prompt issue detection and resolution.
• Cross-Functional Collaboration: Positive feedback and alignment with product, engineering, and platform teams.
• Process and Innovation Contributions: Development of reusable tools and frameworks to improve the ML lifecycle. Apply link
