Who you are
You are likely a commercial due diligence consultant, with 2-5 years’ experience, looking to deepen your understanding and insights into the fields of data and analytics, data monetisation, and the valuation of data, specifically.
It’s highly likely that you have worked on projects where you have seen both the potential and commercial impact of data and analytics to business models, product development, and growth. And in each of these instances, your curiosity and business acumen has wished you could dig deeper.
You will have developed a keen interest in the value derived from digital transformation across different sectors and have an ambition to build on traditional due diligence to validate and offer value creation recommendations across the data ecosystem.
You will draw on your demonstrable M&A experience to lead data due diligence projects (buy and sell), using your commercial acumen to build a bridge between the worlds of business and data. Thereby, enabling our private equity and corporate clients to make better informed investment decisions – that balance defensive and offensive data strategies – to validate and realise their investment thesis.
The skills you have
As a Data Due Diligence Lead, you'll need to:
lead due diligence assignments, working closely with clients and colleagues to validate, value, and make value-creation recommendations derived from the data ecosystem of the target
assess how effective is the target company at leveraging data & analytics to power its business and operational models
identify client issues and use data to propose solutions for effective decision making, automation, augmentation, etc.
assess the functioning of algorithms to ascertain the quality, reliability, speed, and effectiveness of outputs, together with how proprietary the algorithmic solution is
evaluate the effectiveness of data sources, data infrastructure, and data-gathering techniques and recommend improved data collection and storage methods
appraise data teams, processes, methodologies, data literacy and data culture for capability and capacity gaps, and make recommendations for sustained improvement
maintain clear and coherent communication, both verbal and written, to better understand data needs and report results
listen hard
create clear, well-structured reports that articulate compelling stories about how clients work with data, using DataDiligence’s frameworks
horizon scan to stay up to date with the latest technology, techniques and methods
stay insanely curious and enthusiastic about using data and analytics to solve business problems and enthuse others to see the benefit of your work.
identify, document, and communicate insights, some of which will also be used to create and maintain marketing plans and collateral - including web updates, social media campaigns, industry events, etc.
In this leadership role, you will also need to:
recruit, train and mentor data associates and other colleagues
show meticulous attention to detail; self-review and review the outputs of others
contribute to the organisation's overall strategy
be adaptable, well-organised, and able to relate to and grow the team around you
establish new systems and processes and look for opportunities to improve the flow of data within DataDiligence
evaluate new and emerging technologies
represent the company at external events and conferences
build and develop outstanding ‘client hands’ and relationship building skills
turn complex problems into simple stories and explanations with your excellent analytical and problem-solving skills
The qualifications you have
You'll likely have a post-graduate degree in a business, economics, engineering, computer science, mathematical or science-based subject, plus hands-on due diligence experience derived while in a management consulting role.
Management and/or technology consulting experience is highly valued.
What to expect
DataDiligence, and data science more broadly, is highly collaborative. We love to share ideas, insights, and methodologies. You will be expected to share concepts and solutions with the team.
Data science embraces ambiguity, iteration, and continuous improvement. As a small business, we work on the same principles.
Our clients are often businesses of size but, don’t necessarily have advanced data capacity in-house. So, we frequently play a role of educating people and teams to the benefits of big data and analytics, plus proactively transfer skills – thus working ourselves out of clients. This also means that you should expect to be a data ‘cheerleader’ and economic-value advocate.