About the Role
As a Data Scientist in the AI COE, you will be applying a breadth of tools, data sources, and analytical techniques to address high-impact business questions. This role involves combining analytics, design, and AI/ML frameworks to enhance customer experience by understanding, tracking, and predicting sequences of events and interactions. You will collaborate closely with engineering and product teams to ensure data science solutions are aligned with product delivery. A core part of your responsibility will be to use predictive analytics and data mining to solve complex problems and drive business decisions, as well as design experiments, test hypotheses, and build actionable models to optimize last-mile business processes. You will also be responsible for drawing relevant inferences and insights from data, including the identification of trends and anomalies.
Responsibilities
- Apply a breadth of tools, data sources, and analytical techniques to answer a wide range of high-impact business questions.
- Combine analytics, design, and AI/ML frameworks to improve customer experience by understanding, tracking, and predicting sequences of events and interactions.
- Collaborate closely with the engineering and product team to ensure data science solutions are envisioned along with product delivery.
- Use predictive analytics and data mining to solve complex problems and drive business decisions.
- Design experiments, test hypotheses, and build actionable models to optimize last-mile business processes.
- Draw relevant inferences and insights from data including, identification of trends and anomalies.
Requirements
Experience
- 1-2 years of experience in application of statistical modelling, machine learning, data mining, unstructured data analytics in corporate / academic research environments.
- Experience/knowledge of advanced machine learning techniques such as GBM, random forest, etc.
Required Technical Expertise
- Bachelor’s Degree in Statistics, Math, Comp. Science, Economics, Physics, Engineering or related scientific disciplines.
- Proficiency in statistical and other tools/languages - e.g., R, Python.
- Familiarity with relational databases and intermediate knowledge of SQL.
Preferred or Desired Technical Expertise
- Hands-on experience in developing and delivering machine learning models that work in a production setting.
- Strong data Extraction & SQL Query skills.
- Hands-on experience with visualization tools like Tableau, QlikView, Qlik Sense and others.