Data Scientist
Job Details
About the Company
With operational hubs scattered across Europe, Asia, and LATAM, and its headquarters situated in San Francisco, US, the company boasts a workforce of over 1,000 adept professionals. Spanning across more than 20 countries, ALLSTARSIT offers a diverse range of skilled employees across various verticals, including AI, cybersecurity, healthcare, fintech, telecom, media, and so on.
About the Project
The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.
The candidate must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms, and creating/running simulations. The candidate must have a proven ability to drive customer results with their data-based insights. The candidate must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Specialization
Headquarters
Years on the market
Team size and structure
Current technology stack
Required skills:
- 5+ years of experience developing ML solutions in production environments.
- M.Sc. in computer science, statistics, or other similar fields.
- Good coding skills (preferably in Python).
- Deep understanding of Tabular data models, working with imbalanced data, model explainability, noisy labels, etc.
- Has mileage with different aspects of MLOps – model versioning, monitoring, serving, etc.
- Experience with CV models (face and object detection) – advantage.
Other:
- Excellent communication skills in English (verbal & written).
- Independent, proactive, getting things done attitude.
Scope of work:
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive new product solutions.
- Mine and analyze data from company databases to drive optimization and improvement of product development, improving existing models, and developing new models.
- Assess the effectiveness and accuracy of new data sources and data-gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
- Develop company A/B testing framework and test model quality.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.