Data Scientist

Responsibilities

- Effectively engage with stakeholders to understand their business problems and then formulate a data-driven approach for resolution.

- Perform hands-on analysis and conduct in-depth investigations with the team, assist/lead & execute end-to-end measurement projects, and make actionable recommendations to the business.

- Actively look for areas of potential optimization/ automation and implement these changes.

- Document and follow existing processes to reporting and data quality management.

- Continuous research and improvement to become subject matter expert on our data repositories/ analytic solutions. Provide­­ thought leadership to the team on use and interpretation.

- Build predictive models and machine learning algorithms. Propose solutions and strategies to business challenges.

- Ability to communicate with non-technical/ technical peers.

- Provide ad-hoc data and analytics support to the business and perform other related duties as assigned.

- Inherently curious about data with a strong desire to keep up to date with the latest developments in analytics/ visualization and machine learning.

Qualifications/ Skills

- Bachelor's degree in a quantitative field (e.g., statistics, economics, mathematics, business administration, marketing).

- 4+ years of experience in data analytics/ integrated marketing analytics and measurement, working closely with business functions.

- Knowledge of predictive modeling concepts, machine learning approaches, clustering, regression, classification techniques, recommendation system and optimization algorithms is preferred.

- Strong understanding of mathematical and statistical concepts. Experience with utilizing advanced mathematical, statistical and data mining techniques to collect data, analyze and construct solutions for complex business problems.

- Programming skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL.

- Experience in the retail/ fnb industry is highly desirable but not mandatory.

- Attention to details.

- Critical thinking.

- Can-do attitude.

- Decent communication skills, describe findings to a technical and non-technical audience.