What are the responsibilities and job description for the Senior Data Scientist position at Dynam.AI?
Senior Data Scientist (Machine Learning)
This is a full-time remote position.
At Dynam.AI, we're looking for a Senior Data Scientist to become a core member of our science & analytics team. The ideal candidate will help unlock the full power of our clients’ data by building and enhancing our statistical and Machine Learning modeling capabilities to influence various parts of the customer lifecycle, including lead management, customer acquisition, retention, and engagement. Fueled by data, our highly skilled and collaborative teams drive our platform. We make it easy for growth-oriented companies to expand their reach with our fully-managed, end-to-end solutions from proprietary technology to marketing and infrastructure services.
Dynam is using a combination of Data Science, Machine Learning and Exact Sciences to solve hard problems for its clients. As we grow, Dynam.AI looks to welcome new team members excited to work in a dynamic and high-growth environment that celebrates innovation and analytical thinking. Our workplace consists of an inspiring community of people from unique and diverse backgrounds, and our culture is built upon a foundation of respect and camaraderie.
Responsibilities
- Drive the client engagements end-to-end from discovery to delivery.
- Gain a deep understanding of the client’s data and business objectives.
- Lead or help lead the feasibility studies, roadmap generation, research, model architecture and implementation, and delivery of solutions and reports.
- Maintain the dialogue with the client to maximize the transparency and the utility of the results and solutions for the client, yet preventing the scope creep.
- Architect, design, develop, validate, and deploy data models and machine learning models.
- Develop and patent or publish novel methods in data science and machine learning
- Brainstorm hard problems with the Dynam.AI Science and Engineering Teams.
- Efficiently collaborate with domain experts.
Required Qualifications
- Ph.D. or M.S. in Data Science, Computer Science, Math, Statistics, Physics, Engineering, Biology, Neuroscience, Economics, or related quantitative field.
- 3 years of proven industry experience in Data Science and Statistical Data Analysis projects.
- 3 years of proven experience deploying algorithms in a production environment
- Both theoretical and applied knowledge of Machine Learning and AI.
- Advanced proficiency in Python, including statistics, data science, and Machine Learning modules.
- Experience with databases, data analysis, large datasets.
- Deep understanding of mathematical principles of science and engineering, including signal processing, experimental design, data analysis, and statistics.
- Experience in startups, rapid prototyping, and innovating in a small dynamic group.
- Proven experience working with client data (not coursework).
Who is Dynam.AI?
Dynam.AI provides customers across the globe with platform-enabled AI solutions built to uplevel any organization in any industry. Dynam.AI's detection, prediction, and optimization technologies have emerged from years of intensive research and development by a team of world-leading AI physicists and engineers. Dynam.AI's suite of AI-enabled solutions is uniquely adaptable to tackle specific business needs, all while setting the industry standard in precision and accuracy. Dynam.AI is a portfolio company of Analytics Ventures, named Best VC for Artificial Intelligence by Awards.AI.
Dynam.AI's scientists work on a diverse set of problems and data sets. We custom develop and deploy state-of-the-art techniques in Data Science, Computer Vision Machine Learning, Physics Informed Machine Learning,, explainable AI, time-series prediction, and anomaly detection, among others. Employees get ownership in Dynam.AI through a generous stock option plan. Dynam.AI provides ample opportunities for career growth and taking on leadership roles. Our mentoring program enables employees to develop new skills and hone their existing ones in the fast-paced world of AI innovation.