What’s the hardest data problem you’ve tackled?

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Anonymous · Accepted Answer

This's an interesting question. For me, the hardest data problem would not be
the technical challenge but more the business understanding and matching the
recommendations against the business objective.

When I was working at my previous company, I was staffed on a project looking
for automating the procedure on auditing investment fund companies and scaling
the solution as a package that would be applicable to not only 1 specific client
but also cover most of the common areas among all fund managers in the market.

I need to build up the domain knowledge in a very short span of time, becoming
an expert on analysing investment fund performance, covering all different
angles of the performance assessment, such as what the holding of the funds
would be and the impact of different action types such as applications,
redemptions, reinvestment, and the role of financial instruments such as forward
exchange contract, bond, cash, etc. on the position of the fund, etc. All that
business knowledge requires years of experience to absorb, and it'd be
impossible to learn within a short timeframe.

To overcome this challenge and bridge the domain knowledge gap, I was not only
spending time to do self-research but also decided on reaching out to
stakeholders, sitting down with them to actually unpack each item in detail.

After having a proper understanding of a certain item, I started to prototype
the solution to play back with the stakeholders and clearing each item one by
one and getting their feedback to ensure the solution I offered aligns with
their expectations.

That experience taught me a lot on the crucial role of scope alignment,
understanding the right problem to be solved.

What’s the hardest data problem you’ve tackled?

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