What are the responsibilities and job description for the AI Data Scientist position at DeepRunner AI?
About The Role
We are seeking a highly motivated and skilled AI Data Scientist to join our growing team. You will be responsible for the entire data lifecycle, from acquisition and cleaning to processing and preparation for training our cutting-edge AI models. A key focus of this role will be developing innovative synthetic data generation techniques to augment existing datasets and improve model performance. You will play a vital role in building robust and scalable data pipelines that power our AI-driven automation solutions.
Key Responsibilities
Essential Requirements:
We are seeking a highly motivated and skilled AI Data Scientist to join our growing team. You will be responsible for the entire data lifecycle, from acquisition and cleaning to processing and preparation for training our cutting-edge AI models. A key focus of this role will be developing innovative synthetic data generation techniques to augment existing datasets and improve model performance. You will play a vital role in building robust and scalable data pipelines that power our AI-driven automation solutions.
Key Responsibilities
- Manage the entire data lifecycle from acquisition and cleaning to processing and preparation
- Develop innovative synthetic data generation techniques using generative models (GANs, VAEs)
- Design and implement robust data pipelines using modern orchestration tools
- Perform data acquisition through web scraping, API integration, and database querying
- Execute data cleaning, normalization, and preprocessing for various data types
- Implement data quality monitoring, validation techniques, and governance principles
- Create data visualizations and work with feature engineering platforms
Essential Requirements:
- 3 years of experience in data science, with a focus on data preparation and feature engineering
- Strong proficiency in data acquisition techniques, including web scraping, API integration, and database querying (SQL and NoSQL)
- Expertise in data cleaning, normalization, and preprocessing techniques for various data types (structured, unstructured, time-series)
- Proven experience in synthetic data generation techniques, including generative models (GANs, VAEs) and data augmentation methods
- Solid understanding of data pipeline architectures and tools (Apache Airflow, Luigi, Prefect)
- Proficiency in Python and experience with data science libraries (Pandas, NumPy, Scikit-learn)
- Experience with cloud-based data storage and processing platforms (AWS S3, Google Cloud Storage, Azure Blob Storage)
- Strong problem-solving and analytical skills
- Bachelor's Degree in Computer Science, Statistics, Mathematics, or related field
- Experience with big data technologies (Spark, Hadoop)
- Experience with data quality monitoring and validation techniques
- Experience with data governance and data privacy principles
- Experience with feature stores and feature engineering platforms
- Experience with data visualization tools (Tableau, Power BI)
- Competitive salary with equity participation
- Comprehensive health, dental, and vision coverage
- Flexible work arrangements and remote options
- Professional development and conference attendance
- Work with cutting-edge data and AI technology