Careers

Data Science, Principal

Posted 5 months ago

Our client a top financial institution is currently seeking a Data Scientist aiming at solving business problems by model building and insight driven and a Machine Learning Engineer in deploying the models in different production environments; accountable for the end-to-end solution start from distributed data setting and robust result predictions.
The candidate will be an insights-driven analytics leader to support company’s key initiatives and help chart the course for the continual evolution of the organization. S/he will be responsible for the overall data analytics strategy and roadmap for advance analytics services design and implementation.
Roles and Responsibilities:
Functional Duties
• Provide vision for shaping analytics and data science functions
• Partner with architecture team, application teams and data analytics platform team to streamline our systems architecture, tech stack, and internal framework to support a central analytics function
• Develop the framework for analytics across the company – standardization of data collection, data automation, data management, data use and model governance
• Evangelize the use of data-informed decision making through the organization and create data-driven standards for leveraging data science and analytics to offer both internal and external actionable insights
• Lead efforts to select and implement the technologies required to support HK Analytics requirements
• Drive technology investments that utilize analytics as strategic tool
• Define the most important growth metrics that track the business’s performance across different functions and utilize those to affect change
• Partner with stakeholders within the organization to identify and execute on analytical needs/gaps
• Design data solutions for various business functions
• Promote re-use and cross business function awareness of best practices, challenges, etc.
• Build and launch excellent productionalized, low-maintenance models
• Explore and leverage state of the art machine learning techniques for a variety of problems at the intersection of Machine Learning
• Experience working with business stakeholders and users, providing research direction and solution design and writing robust maintainable architectures and APIs
• Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
• Develop, maintain and enhance ML solutions that are highly usable, scalable, secure, and able to be utilized in high volume distributed data
People Management Duties
• Direct activities of a team of data scientist and analysts, and project team members
• Identify, train and develop potential data scientists.
• Implement staff management activities to align with company directive
Minimum Job Requirements:
Education & Experience
• Master degree or above in relevant fields (Mathematics and Statistics for Data Scientist; Computer Science and Engineering for Machine Learning Engineer)
• 10+ years of relevant experience
• Excellent analytical capability and understanding of various AI and analytical techniques
• Knowledge of programming languages like SQL, Python, R, and Scala
• Experience with big data open source solutions such as Spark
• Demonstrated skill, comfort, and success in leading teams to deliver on analytics projects
• A track record of using quantitative analysis to inform commercialization decisions and product roadmaps
• Ability to visualize data in the most effective way possible for a given project or study
• A strong data storyteller
• Demonstrated business acumen, analytical skills and ability to link strategies to business priorities and initiatives
• Proven track record of delivering results in a dynamic high-growth environment with aggressive timelines
• Ability to proactively identify gap and address data analytics related issues
• Ability to learn and adapt quickly to new business domains and technologies
• Ability to conceptualize and articulate ideas clearly and concisely
• Hands-on experience with modern enterprise data architecture and data science toolkits

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