What are the responsibilities and job description for the Senior Data Scientist position at Azurity Pharmaceuticals, Inc.?
- Azurity Pharmaceuticals, Inc. is a fast-growing pharmaceutical company focusing on the needs of patients requiring customized, user-friendly drug formulations, especially children and the elderly. Azurity’s products have benefited millions of patients whose needs are not served by other commercially available therapies. For more information, visit www.azurity.com.
- Mission:
- Use the data prepared by the Data Engineer to run analysis using different tools and methodologies and provide the Advanced Analytics outputs needed to solve the business problem
- Draw insights from large or complex data sets to solve business problem tackled with use case
- Help driving advanced analytics thinking and methodologies by investigating various topics and sharing insights with broader Advanced Analytics and business stakeholders
- Tasks & responsibilities:
- Gather business requirements, translate them into information solutions and identify required data structures and apply strong expertise in advanced analytics techniques (e.g., machine-learning) to design, prototype, and build solutions to use cases
- Ensure robustness and quality of analytics tools & methods used in projects
- Collaborate with Data Engineer to support the data modelling and testing during projects
- Ensure frequent communication with other stakeholders to drive use case solution with business focus and manage expectations on possibilities and lead times
- Collaborate with business ([function]) to provide technical guidance related to advanced analytics models
- Develop best practices for analytics (models, standards, tools) and share learnings with peers
- Contribute to build further the advanced analytics capabilities of Advanced Analytics, attending conferences, allocating time to investigate new topics, etc.
- Knowledge & experience:
- 5 years of experience in a statistical and/or data science role
- Expertise in advanced analytical techniques such as descriptive statistics, machine learning, optimization, pattern recognition, cluster analysis, segmentation analysis, etc.
- Experience using analytical tools and languages, e.g., Python, R, Matlab, etc.
- Experience working with large data sets and distributed computing tools (e.g., Hadoop, Hive, Spark, ...)
- Knowledge of industry and ability to translate business needs into advanced analytics solutions
- Communication skills for highly technical discussions as well as understanding the needs of less technical stakeholders
Benefits:
Maternity & Paternity Leave, Health Insurance