Head of Data and Analytics (Life Insurance Project)

Job Purpose

- The job holder ensures that all systems meet The business/company requirements as well as industry practices.
- The job holde integrate up-and-coming data management and software engineering technologies into existing data structures.
- The job holde develop set processes for data mining, data modeling, and data production.

Key Accountabilities (1)

- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, and ensuring the data platform can ingest data at scale. Assemble large, complex data sets that meet functional / non-functional business requirements.
- This involves collaboratively working with different technology, risk và compliance and segment teams across TCLife to ensure priorities are well understood and proper expectations are established with business stakeholders;
- Collaborate with System and Data Architects, translate complex functional and technical requirements into detailed architecture, design and high performing capabilities with the Enterprise Data Lake
- Design and execute the build-out of data patterns and services - both batch, real-time and complex event handing - leveraging open technologies and in support of the business's requirements
Data Architecture
- Design data architecture and data platform
- Facilitate connectivity, create networks, firewall rules
- Deliver fault tolerance and redundancy
- Develop operational solutions:
- Investigate and understand root causes for issues in business operations
- Initiate continuous process improvements over operational effectiveness
- Anticipates operational problems by studying modes of operation
- Develops operational solutions by defining, studying, estimating, và screening alternative solutions; calculating economics; determining impact on total system
- In charge of Identity và Access Management Security
- Manage dependencies, coordinate delivery và schedule sw/code deployment
- Prepare and execute test scenarios, log defects, evaluate quality risk, report potential impact

Key Accountabilities (2)

Data Engineering
- Turn Business Requirement Documents (BRD) from Financial Analyst (FA) / Business Analyst (BA) to FRD (Functional Requirement Documents)
- Perform technical metadata (source @ target mapping, schemas, instr.)
- Develop data pipelines and microservices
- Develop and maintain the in-house customer framework for the Deep Learning (DL)
- Define and maintain the enterprise-wide Deep learning architecture and infrastructure roadmap
- Lead the solution and ensure that new projects are in-line with the business IT blueprint and their design fits with the DL arch roadmap
- Sets up, develop and maintain an Machines Learning (ML) enabled eco-system including job orchestration, feature store, fitting models, hyper parameter tuning methods
- Productionizes Machines Learning models to meet high-demand and strict SLAs
- Review quality specs và tech design docs to provide timely and meaningful feedback
- Create detailed, comprehensive and well-structured test plans and test cases
- Estimate, prioritize, plan and coordinate quality testing activities
Data Solution
- Analyze user requirements and manage demand for current or proposed projects based on numerous key characteristics
- Coordinate with upper management/BU and prioritize product backlog
- Perform budget estimation và planning; Plan, oversee and lead projects;
- Finalize and perform a BRD (Business Req. Doc.) for user sign-off

Project 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.

Key Accountabilities (3)

PEOPLE MANAGEMENT
- Oversee human resources planning and execution (headcount & costs) of their function
- Attract, onboard and retain the right talents for a high- performing team
- Establish and communicate function and individual KRAs/ KPIs, goals, action plan, expectations and results to reporting line
- Manage function performance & provide feedback regularly (following the annual performance management cycle);
- Define team’s capability requirements and enable team member’s professional and personal development through capability assessment, training, coaching & feedback, mentoring, etc.
- Motivate and recognize team members’ contributions towards the team’s shared goals
- Identify and monitor personal, professional development and career advancement of talents in the function
- Act as a role model and promote corporate culture at function level
- Understand & communicate relevant HR offerings to team members.

Success Profile - Qualification and Experiences

Qualifications
- Bachelor's or Master’s degree in statistics, mathematics, quantitative analysis, computer science, software engineering or information technology.
Work Experience
- 14+ years of relevant experience with modern data capability including scripting, developing, debugging and using big data technologies (e.g. Hadoop, Spark, Kafka or Tableau), database technologies (e.g. SQL, NoSQL, Graph databases), and programming frameworks (e.g. Python, R, Scala, Java) including 10+ years of equivalent managerial roles.
- Deep experience in designing and building dimensional ETL processes, data models, data warehouse concepts and methodologies, optimizing data pipelines and architecture
- Deep experience monitoring complex data issues, evaluating algorithmic approaches and examining data to resolve issues
- Deep understanding of Information Security principles to ensure compliant handling and management of data
- Advanced analytical and project management skills (DevOps, Extreme Programming, Agile, and Waterfall) for a variety of tasks or projects. Ability to deal with complex problems involving multiple facets, variables and situations where only limited standardization exists
- Extensive expertise in data technologies and the use of data to support software development, advanced analytics and reporting. Exposure to cloud technologies is a plus.
Other requirements
- Proven track-record in leading company-wide digital transformation initiatives and change management
- Mastery in Data và Analytics and is an industry expert on the latest data-related technology trends