Data Scientist II identifies business trends and problems through complex big data analysis. Interprets results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining independently. Being a Data Scientist II designs, develops and implements the most valuable business solutions for the organization. Prepares big data, implements data models and develops database to support the business solutions. Additionally, Data Scientist II may require an advanced degree. Typically reports to a manager. The Data Scientist II occasionally directed in several aspects of the work. Gains exposure to some of the complex tasks within the job function. To be a Data Scientist II typically requires 2 -4 years of related experience.
Data Scientist II Job Description Template
Our company is looking for a Data Scientist II to join our team.
- Integrating ML capabilities into production system at scale;
- AI/ML Model creation and experimentation;
- Feature engineering and data engineering;
- Data analytics and insight generation;
- Domain knowledge understanding;
- Collaborate with Microsoft Researchers on strategic projects;
- Author technical papers and presentations, and publish them internally and externally.
- Ability to integrate a wide range of data sources and analysis to answer core business questions;
- You will grow professionally; expand your skills and curiosity; be creative; also help others become their best;
- A Bachelor/Master’s/PhD degree in Computer Science, Mathematics, Statistics, or a related technical discipline;
- Strong customer focus and passionate about doing the right thing for the customer;
- Experience in machine learning using frameworks such as Python’s scikit-learn or PySpark’s mllib;
- 2+ years of relevant data platform, data pipeline experience;
- Experience in statistical packages and standard libraries in Python and/or R;
- Excellent communications skills – able to present and discuss data models and analysis to a range of audiences, in a concise and effective manner;
- 2+ years of relevant data analysis and/or applied ML experience in the context of Data Science.