- Permanent Role
- Growth & Leadership Opportunities
About Our Client
Our client is a leading technology service firm with a reputable presence in Asia Pacific. The brand is known to provide differentiated and end-to-end technology services to government bodies and enterprises.
- Translate customer pain-points into problem statements, architect analytics solution, and engagingly present results and learning's to both technical and non-technical audiences.
- Develop and manage entire end-to-end life cycle of scoping of data inputs, data cleaning and pre-processing, feature engineering, building models, deploying to production and improving models by iterations
- Present statistically sound model validations to justify model selection and performance
- Build and deploy highly valuable, efficient, scalable advanced analytics models in production systems
- Design and develop sophisticated visualizations and dashboards to explain the actionable insights
- Contribute to the data architecture engineering decisions to support analytics.
- Work closely with project manager and technical leads to provide regular status reporting and support them to refine issues/problem statements and propose/evaluate relevant analytics solutions
- Work in interdisciplinary teams that combine technical, business and data science competencies that deliver work in waterfall or agile software development life cycle methodologies
The Successful Applicant
- Post Graduate Degree (Masters or PhD) in Mathematics, Applied Statistics, Business Analytics or equivalent
- At least 3 years of experience in advanced analytics delivery
- Ability to communicate complex quantitative analysis in a concise and actionable manner
- Proficiency in manipulating and analysing complex, high-volume, high-dimensional data (structures/unstructured) from varying sources
- Strong knowledge in Feature Selection/Extraction on a variety of data types
- Strong competency in various machine learning techniques (supervised/ unsupervised learning)
- Expertise in Python/R, Apache Spark (or similar scripting language) coding capability to operationalize data analytics work-flows & processes
- Experience in data visualisation tools and libraries such as Tableau, Qlik, Shiny Plotly, ggplot2, etc
- Experience in machine learning model management and deployment tools using containerization (Docker, Kubernetes)
What's on Offer
Working in a reputable organisation that ensures their staff are given growth and leadership opportunities.