Research Scientist (Data) (The Data Innovator)
ZipRecruiter, San Francisco, CA, United States
Job Description
Are you passionate about using data to push the boundaries of knowledge and create innovative solutions? Do you excel in researching new methodologies, algorithms, and models that unlock data's potential? If you’re ready to shape the future of data science and lead cutting-edge research, our client has the perfect role for you. We’re seeking a Research Scientist (Data) (aka The Data Innovator) to drive data-centric research projects, develop novel algorithms, and explore advancements in machine learning and AI.
As a Research Scientist at our client, you’ll work with a team of data scientists, engineers, and other researchers to develop pioneering data solutions and publish influential research. Your expertise in data modeling, statistical analysis, and AI will be crucial to creating models and insights that transform how data supports business strategies and technological innovations.
Key Responsibilities:
- Conduct Advanced Data Research and Development:
- Lead research on machine learning algorithms, statistical models, and data analysis techniques to solve complex problems. You’ll experiment with novel methods to improve data processing, model accuracy, and predictive capabilities.
- Develop and Prototype New Algorithms:
- Create and prototype algorithms that advance the organization’s data capabilities, including areas such as predictive modeling, deep learning, NLP, and reinforcement learning.
- Collaborate with Cross-Functional Teams:
- Work closely with data scientists, engineers, and product teams to integrate research findings into scalable products. You’ll bridge the gap between theoretical research and practical application.
- Publish Research and Contribute to Scientific Knowledge:
- Publish research findings in top-tier journals and present at conferences. You’ll contribute to the broader scientific community and build a reputation as a leader in data science research.
- Evaluate and Implement New Technologies and Tools:
- Stay current with advancements in data science, machine learning, and AI. You’ll evaluate and test new tools, frameworks, and platforms that could enhance research and data capabilities.
- Develop Metrics for Model Validation and Performance:
- Establish metrics to assess and validate research models’ accuracy, efficiency, and scalability. You’ll ensure models are rigorously tested and optimized for real-world performance.
- Mentor and Guide Junior Researchers:
- Mentor junior data scientists and researchers, guiding them through complex data research and fostering a culture of continuous learning and experimentation.
Requirements
Required Skills:
- Research and Analytical Skills: Extensive experience in data science research, with a strong understanding of statistical and machine learning algorithms, including supervised, unsupervised, and reinforcement learning methods.
- Programming Proficiency: Expertise in programming such as Python, R, or Julia, and experience with libraries like TensorFlow, PyTorch, or Scikit-learn.
- Mathematics and Statistical Knowledge: Strong foundation in mathematics, statistics, and data analysis techniques. You’re comfortable with complex data modeling and statistical inference.
- Machine Learning and AI Expertise: Proven ability to design and implement advanced ML and AI algorithms, including deep learning, NLP, and time-series analysis.
- Communication and Collaboration: Ability to convey complex ideas in a clear, concise manner, and work collaboratively with technical and non-technical teams.
Educational Requirements:
- Ph.D. or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field. Equivalent experience in advanced research or a specialized area of data science may be considered.
- Publications in reputable journals and conference presentations are advantageous.
Experience Requirements:
- 5+ years of experience in data research or a related field, with hands-on experience designing and implementing models for large datasets.
- Experience in publishing original research and presenting at industry or academic conferences.
- Background in developing data-driven solutions for real-world applications and bringing research concepts to production is a plus.
Benefits
- Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
- Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
- Work-Life Balance: Flexible work schedules and telecommuting options.
- Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
- Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
- Life and Insurance: Life insurance and short-term/long-term coverage.
- Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
- Tuition Reimbursement: Financial assistance for continuing education and professional development.
- Community Engagement: Opportunities to participate in community service and volunteer activities.
- Recognition Programs: Employee recognition programs to celebrate achievements and milestones.