Mô tả

Scope of work:

A. Data Architect

Delivers a modern architecture capable of advancing the overall analytic performance and data-driven strategy of the bank

Design end-to-end data streams, storage, data serving systems and analytical workflows, including overall architecture, capabilities, platforms, tools and governing processes.

• Create, maintain, and communicate positioning/go-forward strategies for the data platform and analytical capabilities/tools.

• Share governance responsibility to ensure alignment to enterprise guidelines for security, auditing, data governance, metadata management, etc.

• Help define/improve best practices, guidelines and integration with other enterprise solutions.

• Review analytic solutions for re-usability, scalability, synergy opportunities and alignment to defined best practices and guidelines.

• Create and evolve big-data and analytic technology roadmap, to align with continuously evolving business needs.

• Monitor technology trends and perform discovery of any new tools/capabilities of interest.

• Benchmark big-data and analytic capabilities with industry analysts and other companies.

• Own strategic technology relationships with technology vendors and external communities/partners.

• Lead education and training for analytics community.

B. Projects Management

• Manage project conflicts, challenges and dynamic business requirements to keep operations running at high performance.

• Work with team leads to resolve people problems and project roadblocks, conduct post mortem and root cause analyses to improve practices for maximum productivity.

C. Talent Development

• Mentor and coach junior members in team to enhance their data capability

• Identify and encourage areas for growth and improvement within the team and support with personal development plan.

Yêu cầu

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Machine Learning, Statistic, Data Science or other related technical disciplines

• 8 to 12 years of relevant experience in demonstrating a high degree of proficiency in designing and developing complex, high-quality big-data platforms serving analytical solutions, including 3+ years in a Big-Data Architecture role designing technology architectures, detailed workflows, best practices and governance guidelines

• English proficiency requirements are pursuant to Techcombank's policy

• Proven track record of delivering scalable, resource intensive, integrated and operational big-data and analytical solution; experience creating point of views, roadmaps, and process diagrams

• Hands-on experience working with open-source big-data/data-lake like Hadoop, Spark, Kafka, SQL/NoSQL K-V/Columnar/Graph, ESB and analytical technologies like R/Python, TensorFlow and/or BI tools like Tableau/Power BI; Cloud analytics platform experience preferred

• Experience in Agile Software Development and having a strong understanding of Agile principles, practices and Scrum methodologies

Computation Modelling - Level 2

Utilises new and advanced statistical models to enable the production of business insights and intelligence.

• Conduct statistical modelling of data to derive patterns / solutions.

• Run linear regression models and different types of algorithms for analysis.

• Explain the features and applicability of various data models to junior team members.

Data Analysis - Level 4

Leads hypothesis testing based on data available, derives inferences, patterns or solutions to provide a point of view and defines process improvement opportunities.

• Demonstrate hypothesis testing and explain the statistical significance.

• Build algorithms and work with machine learning/deep learning tools to deliver advance analytics solutions.

• Differentiate among data analytic approaches (descriptive / diagnostic / predictive / descriptive analytics).

• Lead the identification and interpretation of meaningful and actionable insights from large data and metadata sources.

• Evaluate prospective analytical tools and platforms for their functional capabilities and ability to meet requirements of the analytc environment.

Data Management - Level 4

Shares the latest development of data management and translates complex data extraction issues into workable solutions for the team.

• Review processes and tools designed to monitor and analyze model performance and data accuracy.

• Oversee the consolidation and extraction of unstructured and diverse Big Data sources.

• Collaborate with others Data Scientists and Engineers to build complex, technical algorithms in data analytics software applications to improve work efficiency.

Reviews the policies and processes to integrate, access, share and link information across the organization to drive operational effectiveness.

• Lead discussions to understand data requirements and create re-usable data assets for faster deployment of machine learning models.

• Design, build, and maintain optimized data pipelines and ETL solutions as business support tools in providing analysis and real time analytics platform.

Data Management - Level 4

Shares the latest development of data management and translates complex data extraction issues into workable solutions for the team.

• Review processes and tools designed to monitor and analyze model performance and data accuracy.

• Oversee the consolidation and extraction of unstructured and diverse Big Data sources.

• Collaborate with others Data Scientists and Engineers to build complex, technical algorithms in data analytics software applications to improve work efficiency.

Reviews the policies and processes to integrate, access, share and link information across the organization to drive operational effectiveness.

• Lead discussions to understand data requirements and create re-usable data assets for faster deployment of machine learning models.

• Design, build, and maintain optimized data pipelines and ETL solutions as business support tools in providing analysis and real time analytics platform.

Metadata Management - Level 3

Implements the policies and processes to integrate, access, share and link information across the organization.

• Obtain and integrate data and information from various sources into the firm’s platforms, solutions and statistical models.

• Ensure that data assets are organized and stored in an efficient way so that information is easy to access and retrieve.

Thông tin khác

• Thu nhập cạnh tranh

• Chương trình cho vay ưu đãi dành cho cán bộ nhân viên,

• Môi trường làm việc: gắn kết, hòa đồng, kỷ luật

Nơi làm việc

• 191 Bà Triệu, Hai Ba Trung, Ha Noi