We are seeking a highly motivated and experienced Principal Data Scientist with strong expertise in optimization to join our growing team. As Principal Data Scientist, you will be responsible for leading a team of data scientists, engineers, and machine learning engineers in developing and implementing data-driven solutions to business problems.
Requirements
- Design, create, test, and implement complex models and algorithms that drive analytical solutions throughout the organization.
- Lead a team of data specialists.
- Conduct advanced statistical and other analyses to provide actionable insights, identify trends, and measure performance.
- Collaborate with business analyst and understand business problems to implement scalable and sustainable solutions.
- Coordinate with MIS, Digital Specialists, and Data Engineers to deliver holistic analytical solutions
- Communicates the design, functioning and output of the analytical models/solutions developed.
- Ensure timely analysis and testing for regular maintenance of solutions over time.
- Communicate data insights to stakeholders.
- PhD in STEM field and 2+ years' experience or 5+ years' experience as Data Scientist II
- Well-versed in Data Science models; Advanced knowledge in math, analytics and computer science, knowledge of machine learning methods, statistical models, advanced data science programming.
- Have scientific and industrial maturity while delivering designs and algorithms to make and quantify cross-organization trade-offs.
- Plays a significant role in developing other juniors, acts as a technical consultant to product managers, and is valued as an asset to any data science projects.
- Domain expert and functional advisor for business stakeholders
- Handle most of the day-to-day communications with the product owners.
- Leads all internal meetings as well as weekly or fortnightly reports on the team’s progress.
- Divide their project into workstreams led by Senior Data Scientists and delegate tasks efficiently. Ensure that the project is well executed, and deliverables are completed according to the timeline.
- It is recommended to understand parallelization, scalability, and complexity analysis.
Benefits
- Health and wellness plans
- Retirement contribution
- Paid vacation/holidays
