The work you will do:
- Acquire a comprehensive understanding of business processes and data needs, enabling the design and application of advanced analytics solutions for optimization.
- Design, develop, evaluate, and implement predictive modeling, machine learning, and advanced analytics solutions.
- Utilize data visualization techniques to succinctly present insights, predictions, and analytical outcomes to diverse audiences.
- Contribute to the discovery of novel statistical methods, technologies, and design patterns.
- Collaborate closely with machine learning engineers to facilitate development, experimentation, and continuous integration of ML Models.
- Engage in cross-functional teamwork with business SMEs, analysts, data engineers, architects, DBAs, and infrastructure specialists to create and deliver advanced analytic solutions.
- Comprehensively document requirements, assumptions, methodologies, and strategies, including validation, testing, and implementation plans.
- Ensure adherence to established coding and ML standards, and actively engage with source control and change management processes.
- Maintain up-to-date knowledge of approved enterprise technology and the ML stack.
The skills and qualifications you need:
- Bachelor's degree in Statistics, Data Science, or a closely related field within Computer Science (or equivalent).
- 1+ year(s) of hands-on experience utilizing machine learning to enhance business outcomes, including a strong grasp of methods, design, building, testing, and implementation.
- 1+ year(s) of practical involvement with Database Management Systems, Data Lakes, and cloud-based ML Ecosystems like Spark or Azure Databricks.
- Understanding and hands-on experience with advanced statistics and contemporary machine learning predictive techniques
- Familiarity with data modeling tailored for advanced analytics.
- Ability to actively contribute to the development of machine learning models.
- Possess an intermediate level of knowledge and practical use of modern data science languages, such as Python, SQL, R, Scala, and more.