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This role leads the implementation and execution of data science and advanced analytics products, be it traditional predictive / machine learning models or advanced technology such as AI or Generative AI. He or she will proactively partner with business leaders to analyst and suggest business actions through hidden insights from internal and external data - both structured and unstructured - aligning with company's strategies. This person must be a good data storyteller - expected to communicate the findings to senior management and non-technical stakeholders. Besides, he or she must possess an ability to prioritize incoming tasks and manage team backlog to maximize team capacities based on cost-benefit methodology as well as is able to guide junior team members in both business and technical aspects.

Your Day at Allianz Ayudhya

• Manage data science and advanced analytics team; provide consultation to team members on predictive modeling, AI, and GenAI use cases
• Manage the team backlog to ensure deliverables are of good quality and capable of launching several minimum viable products to solve business problems
• Implement predictive modeling and perform ‘what-if’ analysis, using statistics and machine learning knowledge in multiple business areas
• Explore and examine through big data from multiple sources and discover hidden insights
• Use business acumen to communicate findings to business leaders, question existing assumptions and communicate informed conclusions and recommendations
• Lead business meetings, identify key objective from stakeholders and translate objective to model measurement, selecting the right algorithm to use to solve the problem
• Communicate results with data storytelling skills to users, and follow through with execution and present results to senior management
• Co-design and build large-scale, cutting-edge technology and analytic platforms to align with the company’s strategic objectives
• Support department head to plan budget related to advanced analytics
• Manage all IT assets under team and ensure it's up to date
• Working closely with security, risk, compliance, audit team to ensure the gaps can be closed according to the request in the agreed schedule

Must Have

• University degree in Computer Science, Data, IT, Mathematics, Statistics or related fields
• At least 8 years hands-on experience in Data Science/Advanced Analytics/Business Intelligence
• Experience in visualization, statistic methodology, machine learning algorithm for discovering hidden behavior and/or valuable pattern in huge data
• Experience gathering, analyzing and translating business requirements to technical ones ready for implementation
• Experience in working with high velocity data as web log/click, JSON, XML, cookie and other steaming data/ unstructured data
• Experience in working with projects that combines internal and external data (i.e. web, social media) is an advantage.

Nice to Have

• Familiar with machine learning and deep learning tools such as H2O.ai, Spark MLlib, Tensorflow, Pytorch, Scikit-learn and Natural Language Processing and libraries like Spacy, NLTK etc.
• Knowledge of cloud computing (preferably Azure)
• Expertise in programming languages like Python, C++, R or Scala
• Advanced in database management and SQL (of any dialects)
• Big Data technologies (Hadoop, Hive, HBase, Spark, etc.)
• Knowledge of version control systems (e.g. GitHub, GitLab etc.), data pipeline and workflow management tools (e.g. Airflow, Azkaban, Luigi, etc.)
• Data visualization tools (e.g. PowerBI) is a big plus
• Technical experience is an added advantage but not compulsory
• Knowledge of data modelling, database design, data mining, statistical analysis and visualization
• Knowledge of advanced statistics, mathematics, machine learning, artificial intelligence algorithms, relevant data sources and ability to understand potential use-case
• Data modeling, data mining, statistical analysis and predictive analytics
• Experience in data warehousing and relational database technologies, data architecture and open source platforms
• Able to communicate Data insights to non-technical stakeholders; experienced in data storytelling
• Understanding of insurance business and information technology.
• Knowledge in automate testing and unit test

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