Data Scientist-Graph Analytics

2 weeks ago

Pasig, National Capital Region, Philippines UnionBank of the Philippines Full time

The team you are joining

In the AI CoE, we are looking at mid and long-term innovation opportunities driven by AI. A data scientist in the AI CoE will therefore focus on research explorations, new business use cases for the bank and also for the conglomerate Aboitiz. This will entail collaborations internally but also with external partners to leapfrog our innovation opportunities. External partners include universities and research institutes with which we aim to publish peer-reviewed scientific papers.

You will be working with a cross-functional team in ideation and proof of concept activities to uncover new business opportunities with AI, increase revenue, reduce costs, improve quality and performance, and manage risks while ensuring compliance with applicable regulation, laws, or internal guidelines of the bank/Aboitiz.

What you'll do
  1. Individual contributor role who should be able to exercise functional leadership over other data scientists that s/he might work with in UBP or other party.
  2. Develop a good understanding of business operations and easily translate gaps/needs to data science challenges to create quantifiable business impact.
  3. Utilize a variety of modeling tools, statistical analysis, and AI including Machine Learning, Deep Learning, NLP, Graph in developing solutions to guide business decision-making and implementation.
  4. Contribute to one or multiple functional domains of our unit, especially the Graph analytics domain.
  5. The main development stages you will be contributing to are ideation, use case definition and alignment with stakeholders (both internal and external), data collection, model development, testing, POC and prototype/MVP development, supporting for deployment.
  6. Facilitate the data science lifecycle from ideation, data collection to model deployment in collaboration with relevant stakeholders and partners.
  7. Incorporates sound methodology to build, validate and test ML, DL or NLP approaches.
  8. Work both independently and collaboratively with team members and stakeholders with varied background.
  9. Uses our data science platforms and cloud providers to accelerate the progress of our team's work.
  10. Contribute to the AI skill development by structured knowledge sharing, both internally within the team on new technologies and upskill/reskill trainings for UBP, Aboitiz and external stakeholders.
  11. Give presentations at workshops and conferences.
  12. Contribute to and lead scientific publications.
Key Performance Indicators:
  1. Contributed to scientific Graph publications from the unit.
  2. Contributed/led to successful Graph POCs and prototypes.
  3. Supported other teams in deployment of the successful Graph POCs.
  4. Identified valuable Graph use cases that have large impact for the bank because of the application of new AI technologies.
  5. Training and sharing out.
  6. Building, maintaining and leveraging external partnerships to leapfrog our own innovation initiatives.
Who you are
  1. Has proven data science track record in exploring, researching and developing analytical and implementation frameworks and designing tests. Multiple years of experience as data scientist is preferred.
  2. Has knowledge in Python and Machine Learning.
  3. Familiarity with Graph databases and frameworks (e.g. Neo4j, TigerGraph).
  4. Familiar with graph analytics tools (e.g., software, python packages), concepts, and techniques.
  5. Deep understanding of graph structures, traversal techniques, shortest paths, centrality measures and clustering.
  6. Hands-on experience with graph neural networks, graph embeddings (Node2Vec, DeepWalk), PyTorch Geometrics, DGL (Deep Graph Library).
  7. Strong knowledge of machine learning, deep learning and statistical modeling to integrate graph analytics into AI workflows.
  8. Understanding how entities and relationships in graphs influence AI predictions.
  9. Applied graph analytics to cybersecurity, finance and social networks.
  10. (plus) Ability to develop APIs and integrate graph analytics into AI pipelines.
  11. Has excellent organizational, communication, presentation, project management and analytical skills.
  12. Preferred to have a Master's degree in Data Science/Analytics or relevant certifications. At least Bachelor's degree is needed.
Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Information Technology and Research

Industries

Banking

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