Data Scientist

Job Description

REQUIREMENTS

• MSc in a relevant field such as data science, operations research, mathematics, science, data mining, artificial intelligence, applied statistics, machine learning or economics.
• 5+ years experience in Information Systems.
• Hands-on experience in Data Science ecosystem.
• Hands-on experience with big data technologies (Spark and Hadoop ecosystem) and deep learning frameworks (Tensorflow, Keras, etc.).
• Hands-on experience with SQL, R, Python.
• Hands-on experience with DevOps frameworks (Git, CI/CD, Docker).
• Hands-on experience building libraries and packages to be re-used by others.
• Hands-on experience building DS Solutions for production usage.
• Team player with a problem solving attitude.
• Experience of delivering advanced analytical projects to large, complex organisations in a multi-functional environment.
• Able to challenge and review the quality and value generated from analytical output.

RESPONSIBILTIES

• Deliver analytics projects, applying appropriate statistical and machine learning techniques to produce key insights and actionable takeaways, and presenting findings and recommendations to the stakeholders.

• Develop dimensions of the DS project such as data analysis, visualisation and development of tools, models and documentation. Analyse business metrics and KPIs to understand trends, identify issues, and opportunities for optimisation.
• Address day-to-day technical issues, ensuring high quality of deliveries are achieved.
• Derive business insight from large, structured, semi-structured and unstructured, data sets and work with business stakeholders to deploy insights derived from this analysis to extract commercial value.
• Work with cross-functional team members, combining computer science and mathematics, to identify and inject high-value actionable insights into business processes at their point of highest impact.
• Work in quick iterations, using the techniques and algorithms best suited for solving the challenging problems through active involvement in the in the development of our analytics tools for A/B testing, segmentation, funnel analysis, and other analytics needs.
• Support sprint/work design and planning projects to bridge the gap between research and analytics by providing data-driven solutions across the required areas.

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