Siemens Ag is looking for data scientists to tackle real-world challenges and build frameworks for machine learning and GenAI projects to solve business problems.
Requirements
- Proficiency in programming languages such as Python or R.
- Proficient analytical abilities enabling the extraction of practical insights from data.
- Familiarity with machine learning algorithms and/or large language models (e.g., scikit-learn, TensorFlow, PyTorch) and proficiency in implementing such algorithms.
- Good understanding of data visualization tools (e.g., Tableau, Power BI).
- Understanding of prediction model evaluation and validation techniques.
- Proficiency in feature engineering and selection.
- Fundamental grasp of version control systems, Snowflake, and large language models.
Responsibilities
- Assist in data collection, cleaning, and preprocessing to ensure high data quality.
- Build frameworks for machine learning and GenAI projects and use these frameworks to solve business problems.
- Write SQL and Python programs to support data engineering and machine learning use cases.
- Work on visualization tools like Tableau and Power BI to develop user-friendly dashboards and analyze data.
- Collaborate with architects and senior developers to review code and the developed dashboards.
- Document activities in a structured manner that enables carrying forward the project and reducing dependencies.
- Employ Snowflake for the review and analysis of data.
Other
- Current rising senior undergraduate students or current graduate students pursuing a degree or equivalent experience in Data Science, Computer Science, Statistics, Mathematics, or a related field.
- Strong communication abilities and adept at functioning effectively within a team setting.
- Eligible candidates must be located within 50 miles of Alpharetta, GA, and be able to work 40 hours per week from May to August.
- Capability to collaborate successfully with a multicultural and varied team while showcasing leadership abilities.
- Skill to adeptly handle and sequence multiple ongoing activities.
