Key Responsibilities
- Serve as a key client-facing contributor
- Collaborate with the business to translate unstructured business questions into quantitative problems
- Provide advanced analytics support, including machine learning, big data, and sophisticated statistical modeling
- Advise on appropriate analytical models based on available data, technology, and platform
- Evaluate machine learning algorithms and models, and provide technical recommendations to business units for decision-making
- Prototype advanced analytics and machine learning solutions, and optimize them iteratively for business partners
- Monitor data science product performance to ensure the delivery of expected business value, and initiate necessary corrective actions
- Anticipate needs and lead the implementation of capabilities such as data modeling, algorithms, new technology, and partnerships
Requirement:
- Master's degree or equivalent in Data Science, Computer Science, Econometrics, Mathematics, Operations Research, Statistics, or a related discipline
- 3-6 years of work experience in data science, with a proven track record of leveraging large amounts of data to drive significant business impact, including at least 1 year of optimization experience
- Advanced analytical skills, experience in recommending appropriate algorithms and methodologies for problem-solving and decision-making, leveraging both logic and creativity
- Proficiency in statistical analysis tools and machine learning languages, such as Python/R, as well as experience with big data tools (e.g., Spark) and query languages
- Preferred experience in advanced machine learning topics (e.g., NLP, Graph Neural Networks, Probabilistic Models)
- Strong communication skills to articulate ideas verbally and in written form for audiences at different levels
- Solid understanding of the latest analytics technology, concepts, and trends in platforms and tools
- Good knowledge of database concepts, data modeling, business intelligence disciplines, and data management tools
- Experience with the AWS cloud stack is an advantage
- Experience with data visualization tools (e.g., Alteryx, QlikSense, PowerBI) is an advantage