Who you are
As a data associate, you'll need to:
work closely with clients and colleagues to identify client issues and use data to propose solutions for effective decision making, automation, augmentation, etc.
build and/or assess algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation
use machine learning tools and statistical techniques to solve business problems
test data science, machine learning, and analytical methods and models to select the most appropriate ones for use on a project
maintain clear and coherent communication, both verbal and written, to understand data needs and report results
create clear, well-structured reports and proposals that articulate compelling stories about how clients work with data, using DataDiligence’s frameworks
assess the effectiveness of data sources and data-gathering techniques and recommend improved data collection methods
horizon scan to stay up to date with the latest technology, techniques and methods
conduct research from which you'll recommend proof of concepts, mvp, v1.0, etc for client use/advise
look for opportunities to use insights/datasets/code/models across DataDiligence to continuously improve our business (for example in the HR and marketing departments)
stay insanely curious and enthusiastic about using algorithms 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.
As you grow with DataDiligence, you will also need to:
recruit, train and lead a team of data associates
contribute to the organisation's overall strategy
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 relationships with clients.
The skills you have
You'll need to have:
excellent analytical and problem-solving skills
outstanding 'client hands' and relationship building skills, having likely spent time in a consulting role
excellent (generalist) data skills – data understanding, data processing, model building, evaluation, and deployment, data infrastructure, data operations, ML operations
hands-on experience with delivering data projects – as a data analyst, data scientists, data engineer, ML engineer, analytical engineer or similar
exceptional communication and presentation skills in order to explain your work to people who don't understand the mechanics behind data analysis
effective listening skills in order to understand client requirements and business problems
drive and the resilience to try new ideas if the first one doesn't work - you'll be expected to work with minimal supervision, so it's important that you're able to motivate yourself
planning, time management and organisational skills
the ability to multitask, deliver under pressure and to tight deadlines
great attention to detail
team working skills and a collaborative approach to sharing ideas and finding solutions.
The qualifications you have
You'll likely have a degree in a computer science, mathematical or science-based subject. The following degree subjects are particularly interesting to us:
computer science
data science/computer and data science
engineering
mathematics
mathematics and operational research
physics
statistics.
We expect you to have a hands-on experience with data analytics, data science, data engineering, machine learning or similar.
Alternatively, you have a postgraduate qualification in Business and have hands-on experience with data science likely derived while in a management consulting role.
Consulting experience is highly valued.
A postgraduate qualification, such as a Masters or PhD, is useful.
We will also consider candidates with business qualifications who can prove a passion and portfolio of evidence supporting their data science skills.
What to expect
DataDiligence and data science more broadly is highly collaborative. We love to share ideas, insights & 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.