Available to hire
I’m Peter Morian, an actuary and data scientist who loves turning data into practical, data-driven decisions. I lead analytics and ML initiatives across insurance, banking, and government programs, building production-ready models and guiding cross-functional teams to deliver measurable value.
I hold a Master of Data Science and dual bachelor’s degrees in Actuarial Studies and Economics from UNSW. I’m passionate about mentorship, stakeholder collaboration, and delivering actionable insights that improve policy and business outcomes through innovative analytics.
Skills
Work Experience
Manager – Actuarial and Data Science at NDIA
June 1, 2024 - PresentResponsible for developing machine learning models and managing stakeholder relationships in the Assistive Technology stream of the Budget Models project, driving insights for policy and decision-making. Supervised a direct report, mentoring on data science methodologies, project management, and technical skills to foster professional growth and improve team performance. Created and facilitated a two-day Budget Models event planning the team’s workload for the next 12 months and onboarding new starters on the project.
Senior Data Scientist (6 Month Contract) at Neilson Financial Services
September 1, 2023 - March 31, 2024Established the Data Science practice for a global team of analysts, data scientists and actuaries, including defining documentation standards via Confluence and introducing version control via GitHub. Reduced marketing expenses by 11% by building and productionising GLM/GBM models to predict optimal TV advert spot times, using SQL and R. Provided timely insights into sales and operations performance in the UK and Canada to Senior Leaders by developing intuitive PowerBI reports.
Data Scientist at AMP
January 1, 2022 - September 30, 2023Managed and led three analysts, responsible for recruitment, training, mentorship, task allocation and providing ongoing performance feedback. Increased AML/CTF program scope by 17% by modifying ETL data pipelines and data modelling, bringing in previously unmonitored international transactions. Reduced false positive AML alerts by 25% and decreased costs by $300,000 p.a. by implementing a production-ready clustering segmentation algorithm using Python. Discovered hidden money laundering networks amounting to $4,300,000 through a network analysis model using Python and SQL. Collaborated with senior management via ad-hoc analysis and hosted quarterly knowledge sharing sessions, which promoted the reputation and awareness of the Group Analytics team at AMP.
Senior Analyst - Actuarial and Data Science at TAL Australia
November 1, 2019 - January 31, 2022Streamlined turnover time by 60% by developing an automated month-end voluntary premium reporting system in R. Increased automatic Acceptances by 11% and reduced underwriter workload by implementing a Python program that utilizes NLP and a Recurrent Neural Network (LLM) to predict applicant risk profiles. Created an interactive R Shiny dashboard that aided management with understanding the operational and financial impact of a new underwriting framework, resulting in a 16% increase in automatic Acceptances and cost savings of $250,000 per year. Decreased time-to-decision of mental health claims by 10 days by identifying factors causing delays using process mining, survival analysis and ML methods in Python and R.
Actuarial Analyst at TAL Australia
April 1, 2019 - November 30, 2019Produced monthly valuation reports for group Superannuation partners using Excel and Prophet, to analyse and justify movements in IBNR, Profit Share, Capital Reserves and Embedded Value. Led an initiative to transition away from legacy Excel and into R by creating a new RBNA Experience Investigation process and teaching the R language to other team members.
Quantitative Risk Graduate at Westpac
February 1, 2018 - April 30, 2019Supported the Financial Crime Analytics team by creating an interactive geolocation web tool that detects fraudulent logins and falsified customer information using SAS and HTML. Assisted Line 2 Risk with approvals and compliance with prudential capital requirements by producing a Probability-of-Default Credit Risk model. Improved the quality of Westpac’s data reporting standards to be compliant with APS113 and CPG235 by developing a data quality metrics dashboard using Python.
Quantitative Risk Intern at Westpac
November 1, 2016 - February 28, 2017Utilized SQL and R skills to provide detailed analysis of back-test P/L’s (hypothetical and clean finance) against the 1-day VaR, for all trading portfolios, as a part of the Line 2 Market Risk team.
Education
Master of Data Science at University of New South Wales
January 1, 2020 - December 31, 2021Bachelor of Actuarial Studies & Bachelor of Economics at University of New South Wales
January 1, 2014 - December 31, 2017Qualifications
Actuary (AIAA)
January 1, 2021 - December 30, 2025Industry Experience
Financial Services, Government
Skills
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