Job Description
Join DataVista Analytics as a Senior Data Scientist and transform complex data into strategic business insights. We're seeking a visionary expert to lead advanced analytics initiatives that drive innovation and growth in our dynamic tech ecosystem. Collaborate with cross-functional teams to architect data solutions, mentor junior analysts, and pioneer cutting-edge methodologies that reshape industry standards.
Our Austin-based hub offers a collaborative environment where your expertise in statistical modeling and machine learning will directly impact product development and operational excellence. We provide competitive benefits, flexible work arrangements, and opportunities to present findings at international conferences.
Responsibilities
- Design and implement end-to-end machine learning pipelines for predictive analytics and pattern recognition
- Translate business objectives into measurable data science projects using Python, R, and SQL
- Develop A/B testing frameworks and causal inference models for product optimization
- Create compelling data visualizations and executive dashboards using Tableau and Power BI
- Mentor junior data scientists and establish best practices for model deployment
- Lead research initiatives in natural language processing or computer vision applications
- Collaborate with engineering teams to integrate models into production systems
Qualifications
- Master's degree in Data Science, Statistics, Computer Science, or related field (PhD preferred)
- 5+ years of experience in applied data science with proven portfolio of deployed models
- Expert proficiency in Python (scikit-learn, TensorFlow) and SQL with large datasets
- Strong foundation in statistical modeling, experimental design, and causal inference
- Experience with cloud platforms (AWS/GCP) and containerization technologies
- Demonstrated ability to translate technical insights to business stakeholders
- Published research or patents in machine learning or data science methodologies
- Experience with MLOps tools (MLflow, Kubeflow) for model lifecycle management