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Build an Expert Data Science Team
Here's the best kept secret for
finding data experts.
Demand for AI, ML, Analytics & Data Engineers is 5X the supply
How will you find quality data experts to run your AI projects?
Build a World-Class Data Team In Just a Few Days
Learn How Your Growing Company Can Build and Retain AI, Machine Learning, Data Analytics and Data Engineering Teams In a Fast and Cost-Effective Way.
- Stop competing with Silicon Valley giants
- Hire the top 1-3% rigorously vetted engineers in the world
- Tap into continuously up-skilled data experts
- Get your data and AI projects back on tack
- Support your entire AI development cycle with exceptional engineers
The Right Skills. The Right Roles.
Machine Learning Engineering
Data Engineering
Data Analytics Engineering
Data Analysis & Visualization
- Role: Define and deploy AI models; ensure their usefulness in production.
- Top Tools & Skills: Swift, Go, Python, TensorFlow, Pytorch, Recurrent, Convolutional and Attention Architectures, NLP, Computer Vision, Time Series Forecasting.
Role: Manage the entire data lifecycle from various sources and prepare the data for the team when AI models are deployed.
Top Tools & Skills: SQL, Spark, Hive, Airflow, MongoDB, Cassandra, Hadoop, and various AWS services (Glue, Redshift, EMR, DynamoDB)
- Role: Provide clean, tested and documented data sets and data models to end-users across the entire organization.
- Top Tools & Skills: Snowflake, Airbyte, dbt, SQL, Perfect, Python, Looker, Hex.
- Role: Analyze data trends; identify key data insights; ensure business value is delivered by AI projects.
- Top Tools & Skills: Pandas, Scikit-learn, Spark, Tableau, Cube.js, AWS Quicksight, AWS Redshift