Changi Airport Job Vacancies


 Serving tens of millions of customers each year, Changi Airport aims to create memorable experiences by connecting lives. Whether it is growing Singapore’s air connectivity to the world, enhancing experience at the various touchpoints, or curating personalized retail offerings, we are continually striving to better serve our customers at Changi Airport. The talent and commitment of our people makes the dreams that we are chasing a reality.


Enterprise Data Science & Management




Enterprise Data Science & Management (EDSM) comprises of a team of analytics professionals tasked with the mandate to help solve business problems and build up data capabilities across the enterprise. EDSM leverages on data science methodologies and adopts a “data first” approach in distilling actionable insights to key stakeholders including senior management and business teams. EDSM seeks to create positive impact and business value through data-driven decision-making.


We are looking for a Data Science Lead to join our vibrant team in EDSM. Working with passionate data-driven enthusiasts, you will lead the deployment of decision sciences with advanced analytics as well as machine learning and AI capabilities to support various lines of businesses. You will also help to make data-driven analytics and decision-making part of the company’s DNA.


You are a driven leader who has demonstrated success in leading teams to apply data science to deliver positive impact in areas such as revenue generation, cost reduction, commercial innovation or operational efficiency.


Responsibilities




• Lead data science and major data projects to achieve business objectives, taking ownership of model development and deployment.

• Develop an enterprise data science strategy to achieve scale, synergies and sustainability of model deployment across data science teams.

• Undertake rigorous analyses of business problems on structured and unstructured data with advanced quantitative techniques.

• Apply your expertise in data science, statistical analysis, data mining and the visualization of data to derive insights that value-add to business decision making (e.g. hypothesis testing, development of MVPs, prototyping etc).

• Develop and train predictive / ML models using a diversity of machine learning tools and frameworks.

• Partner and support users in various internal teams to solve problems, identify trends / business opportunities and participate in experimentations.

• Distill complex analyses and technical concepts into clear and actionable insights for business and enterprise leaders.

• Coach aspiring analytics practitioners in the company, give talks, conduct trainings and internal workshops to build up in-house data science capabilities.


Requirements

• At least a Masters in Computer Science, Mathematics, Statistics, Operations Research or other quantitative discipline.

• At least 8 years experience in quantitative analysis and data science (machine learning / predictive modelling) with high proficiency in programming languages such as Python or R.

• Ability to grasp business concerns and formulate them as technical problems that can be solved using data and the appropriate toolkit.

• Deep expertise in a range of ML concepts, frameworks and techniques such as logistic regression, clustering, dimensionality reduction, recommendation systems, neural nets etc.

• Strong understanding of data infrastructure technologies (e.g. Spark, TensorFlow etc).

• Familiarity with data engineering methodologies, including SQL, ETL and experience in manipulating data sets with structured and unstructured data using Hadoop, AWS or other big data platforms.

• Highly proficient in data visualization and the use of dashboarding tools (e.g. Tableau, Matplotlib, plot.ly etc).




• Proven track record in delivering bespoke data science solutions in a cross-functional setting.

• Strong project management and organizational skills.

• Excellent written, verbal communication skills and adept at engaging senior management leaders

Apply now

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