OakTree Interview Prep Flashcards
Describe your experience translating complex financial business requirements into detailed technical specifications for data products. Can you provide a specific example where you successfully bridged the gap between stakeholders and data engineering teams?” (Focuses on technical translation and stakeholder collaboration)
Liquidity Analysis at BAM. The risk guys just asked for liquidity data from Bloomberg
Currency Management look throughs at UBS
Rolling futures and FX
“Oaktree operates in the asset management industry. How familiar are you with financial data concepts and the specific data challenges faced by investment firms? Give an example of how you’ve applied this knowledge in a previous role.” (Focuses on industry knowledge)
20+ years working with investment teams
“This role involves owning the end-to-end product lifecycle. Walk me through your process for managing a data product from ideation to deployment and ongoing maintenance. How do you ensure continuous improvement?” (Focuses on product lifecycle management)
1 interviews with stakeholders with detailed notes.
2 Organize notes into user stories and add to kanban board
3 - Engage with development team and product manager
4 - Test new deliveries
5 roll out new deliver
6 add to documentation
“How do you approach defining and tracking Key Performance Indicators (KPIs) to measure the impact and efficacy of new data solutions? Can you give an example of KPIs you’ve used in the past?” (Focuses on data-driven decision making and KPI tracking)
KPI I have used are:
Data adoption rate - who is using the data
Accuracy of the data - Calcualece Z-scores or use Tukey tests to to measure deviation from actual
Timeliness of the data update - Measured via logs
Discrepancy resolution time
“Describe your experience working with data warehouse, data lake, and cloud solutions. How have you collaborated with data engineering teams to ensure accurate and timely delivery of data products?” (Focuses on technical experience and collaboration)
CNA - Different CTO for each line of business and they each chose different RDBMS
UBS and WIlliam Blair - I needed to standardize data from 2 or more accounting systems and then enrich it with look throughs to determine sectos, and currency, or tag a beta with restpect to a benchmark to it.
At BAM we built our bond supply warehouse using Snowflake for easy access to direct share data from Refinitv, but we pulled in pricing and ratings data from redshitft, Sybase, and PostGres
“This role requires strong communication skills to present complex data concepts to senior stakeholders. How do you ensure your communication is clear and effective, especially when dealing with technical information?” (Focuses on communication and stakeholder management)
Use visual aids whenever possible
For status reports I give an executuve summary at the top, and then brek out details below.
At BAM the CDO used my stakeholder status reports as examples on 2 group wide calls.
“Oaktree emphasizes a collaborative environment. Describe a situation where you had to build consensus among diverse stakeholders with differing perspectives. How did you navigate the situation, and what was the outcome?” (Focuses on relationship building and collaboration)
Russian positions after Ukraine invasion
Pms want the model an excel also that they can manipulate it when they want to and make tweaks.But the firm needs it in math.Lambert python to avoid gunsituations
“How do you ensure data quality, SLAs, and lineage are documented and maintained for your data products? Describe your process for addressing data quality issues.” (Focuses on data governance and quality assurance)
Build lineage into the data with data source IDs in the table, import action tables and staging tables
This role requires you to work in an agile environment. Describe your experience with agile methodologies and how you ensure continuous alignment with business goals and objectives in an iterative delivery process.” (Focuses on agile experience)
During my 2 years at BAM I acted as product owner and also as a technicla resource for the data warehouse design.
Created mockups and POCs to agree on design
“Given Oaktree’s fast-paced environment, how do you manage competing priorities and adapt to shifting demands? Provide an example of a time you had to quickly reprioritize tasks and deliver under pressure.” (Focuses on adaptability and time management)
My plate was full of projects to enhance the team in the long term and a fund laucnh came up. We needed simulated holdings, prouect training, etc and we had a client on the line.
Give me 3 examples of data SLA’s
1 Data Accuracy & Completeness
2 Data Timeliness & Ingestion
3 Data Availability & System Uptime
Give me 4 components of an SLA
1 Metrics
2 Measurement (how)
3 Scope
4 Resolution of problems
Can you walk us through a data product you’ve built or managed from inception to deployment? What was the business problem, and how did you measure success?
How would you ensure data quality and accuracy in a financial data product? Can you provide an example of how you’ve handled data integrity issues in the past?
Oaktree works with data warehouses, data lakes, and cloud solutions—can you describe your experience with these technologies and how you’ve worked with data engineers to implement them?
If a front-office team requests a new dataset integration, how would you go about assessing feasibility, defining requirements, and ensuring proper governance?
- Understand the Business Need
What investment or operational decisions will this dataset support?
What level of granularity and frequency do you need?
Are there any existing datasets that partially meet this need?”
- Assess Feasibility
“Next, I’d evaluate feasibility by collaborating with data engineering and technology teams to answer key questions:
Does this dataset exist internally, or do we need to source it externally?
What format and delivery mechanism (API, files, database) are available?
Can our existing infrastructure support this dataset efficiently?”
If the dataset is external, I’d also consider procurement, licensing, and cost implications.
- Define Requirements & Success Metrics
“I would then document the technical and business requirements, including:
Data schema, transformations, and mappings to existing models
Quality expectations (e.g., completeness, accuracy, timeliness)
SLA expectations for data availability and updates
Business rules or calculations needed for usability”
I’d also define success metrics (e.g., reduction in manual effort, improved investment decision-making) to measure impact.
- Ensure Proper Governance & Compliance
“Governance is critical, especially in an asset management firm. I’d work with data governance and compliance teams to address:
Data lineage: Documenting source-to-consumption flow
Access control: Ensuring only authorized teams can use the data
Regulatory compliance: Checking if the dataset impacts SEC, GDPR, or internal policies
Metadata management: Tagging the data for better discoverability and cataloging”
- Iterate, Test & Deploy
“Once feasibility and governance are confirmed, I’d coordinate a pilot phase with key users to validate the data in a lower environment. Based on their feedback, we can make adjustments before full deployment. I’d also track adoption post-launch to ensure the dataset is driving expected value.”
How do you track and measure the adoption and impact of a data product after its launch?
How do you communicate complex data concepts to non-technical stakeholders? Can you share an example where you had to bridge the gap between business and technology teams?
1 Respect the audience
2 Understand the audience -
3 Use business context - maybe explain data loading as a supply chain
4 Use visual aids and storytelling
5 Encourage 2 way communication
Have you ever had to push back on a senior stakeholder’s request for a data feature or product? How did you handle it?
Steve from Austin throwing Tbills into the bond model towards the end of the project. Reminded him of scope but then respected him by investigating.
describe a project where you defined and executed a strategic data solution?
Coral/ART
Bond Supply
How have you approached building and maintaining relationships with cross-functional teams and third-party vendors in your previous roles?
Open communications - Slack/Teams for the project
Transparency
Build Trust - Honesty. deliver. Takes a long time
How do you prioritize features and projects when working on data enablement strategies
Get the value of each task from the stake holders and the time required from the developers. Hit high value, short time committemnt first and then work your thogrou the high value list
Say NO sometimes
explain a time when you had to translate a complex technical concept for a non-technical audience?
Overfitting in machine learning - My daughter memorizing the book instead of learning to read
Database normalization. using IDs instead names to track employees. Married worker in the mailing list, hr list, vacation list
Describe a situation where you identified an opportunity for improvement in a data solution.
What if scenario for risk model
Focus on top selling cars for JD Power
How do you stay updated with emergent technologies, such as AI
Monthly tech breakfasts
Blogs
Coursera
Chat GPT
What strategies have you used to ensure that data governance decisions align with a broader data strategy
Sicav Index compliance log
3/5/10 rule for mutual funds
Data quality tests for incoming data
Give examples of vendor budget you managed
RIMES ETF look through
RIMES Index Data
DataStream
Bloomberg
Bloomberg back office
Cloud Attribution
Tell me about a time when you had to drive adoption of a new data solution or platform.
How do you handle conflicting priorities when managing cross-functional initiatives?
Prioritize based on value
If the priorities are for the same stakeholders I let the stakeholders decide.
When there are different stakeholders I escalate for guidance
Manage Stakeholder Expectations
Document Decisions and Rationales
Describe a project where you had to deliver iteratively.
Coral - One desk at a time
BAM Bond Supply one country at a time
Can you describe a project where you were involved in the design or implementation of a data warehouse?
WB - Data from 2 accounting systems plus look through form vendors and web scraped data
UBS Coral - Data from 3 accounting systems
Both of those I standarized the data into a rigid format and quality checked it as it come in
How do you handle the challenge of data integration from disparate sources into a data warehouse?
Staging areas to receive income data that is timestamped by load date. loads are kept seperate.
Qyualit check data, clean, transfor and then load intot he ware hosue
use datasouirce IDs
How do you approach data modeling for a data warehouse?
Give me an example of a delivery that failed and how you reacted?
Tell me your strengths
Breadth and exposure to investment teams.
I’ve worked as part of an investment team for 20 years sitting next to Portfolio managers and quants.
Worked with a multi-asset team so our needs never fit into the organization either from tech to ops, compliance and reporting.
Mention training trading and accounting at WB
Started an asset management company from scratch. Handled not just tech but operations.
Regarding breadth: I’ve developed and supported systems in both large and tiny organizations.
Tell me your weaknesses
