We're looking for a Data Science Analyst to join our team in London as part of our Consultancy function.
Your Role: This role involves a high degree of visibility to our entire organization and you will be expected to work toward developing end-to-end solutions that increase efficiency through automation or increase the quality of our offering to clients.
This role is wide in scope allowing plenty of time for independent thinking and exploring solutions through exploratory data analysis as well as Data Science feature development for our Saas WARC product, working closely with product managers and software engineers to deploy solutions. At times you will be called to work as a data engineer and build functional, efficient, low-latency ETL pipelines for a feature prototype. Other times you will need to develop SQL queries after cleaning and preprocessing at times complex and unstructured data sets. Mostly you will work towards utilizing sophisticated algorithms and techniques to bring a high degree of accuracy to our machine learning model development and deployment.
An example of some recent projects we have worked on include the following:
- A Llama2-7B RAG (Retrieval Augmented Generation) model fine-tuned on WARC case studies for the prototype of a client facing Chatbot including comparison with “out-of-the-box” sentence transformers
- A hybrid LSTM and Prophet time series forecasting model for advertising expenditures, capturing long-term and short-term trends, at the country, product category and advertising medium level on a quarterly basis
- A cohort-based, collaborative filtering system (user-content matrix) for real-time, personalized content recommendations in customer and prospect marketing emails as well as customized home page experience
Key Responsibilities
- Partner with Business Managers (ie stakeholders) to align on requirements and develop both recurring and ad hoc reports to meet client needs, particularly the VP of Data Science, Director of Product Management, and the CTO
- Contribute software code regularly and ready for peer-review to cloud-based software development and version control repository, such as Github
- Develop scalable and efficient SQL queries and transform data from multiple sources to obtain a unique insight for Business Managers
- Work autonomously and regularly to conduct extensive quality assurance to minimize issues with data or model accuracy, including model output, reports and ad hoc analyses
- Proactively troubleshoot issues in data accuracy in both the database environment and reports
- Identify, analyse, and interpret trends within data to predict outcomes based on business questions/problems and make recommendations to drive performance
- Communicate complex processes and present results in a clear manner to end users
- Utilize Python to design, create, and support forecasting and modelling, contributing intellectually to advancement efforts as well as practically in generating quality code that contributes to our business objectives
- Assist with data annotation, data wrangling, implementation of classifiers using machine learning techniques, validation and updating of these classifiers to ensure optimal performance
- Help serve as a Data Science ambassador always seeking to insert opportunities where technology, machine learning and data analysis can solve complex problems reliably
Your Experience
- Excellent attention to detail
- Strong experience in working in a software engineering environment, generating quality code with reproducible data science outputs that can be distributed, shared and understood
- Strong experience in building, querying, and modifying relational databases such as SQL Server, Postgres, or MySQL and a demonstrated analytics and problem-solving abilities in the context of analyzing large, real-world datasets and model building such as Random Forests, Neural Nets and Support Vector Machines
- Strong experience in working in cloud computing environments such as AWS (preferred), Google Cloud or Microsoft Azure
- Strong experience in developing software in Python and demonstrated ability to create machine learning models and new feature prototypes
- A Bachelors/ Masters in a quantitative field (Statistics, Research, Systems Engineering, Sciences, Maths, Economics etc) would be advantageous but not essential.
- Languages: Python & SQL (required)
- Visualization (one or more): Looker, Data Studio, Tableau
If you don't meet every single requirement, we'd still encourage you to apply. At WARC, we are committed to creating a diverse, inclusive and authentic workplace, so if you are excited about this role we would still like you to apply.
Who are we?
WARC is the global authority on marketing effectiveness. We provide rigorous and unbiased evidence, expertise and guidance to help marketers navigate any challenges effectively. WARC services include 100,000+ case studies, best practice guides, research papers, special reports, advertising trend data, news & opinion articles, as well as awards, events and advisory services.
WARC operates out of London, New York, São Paulo and Singapore to service a community of over 75,000 marketers in more than 1,300 companies in 100+ markets and collaborates with 50+ industry partners.
WARC is an Ascential company. Ascential delivers specialist information, analytics and ecommerce optimisation platforms to the world's leading consumer brands and their ecosystems. We help our customers to make smart decisions that improve performance now, and in the future.
With more than 3,300 employees across five continents, we combine local expertise with a global footprint for clients in over 120 countries. We are listed on the London Stock Exchange.
Why choose us?
At Ascential, diversity, equity and inclusion is core to us. We’re a company built around our people - and we’re committed to supporting each and every one of them to be the best they can be. We love having a diverse team of people who bring new ideas and different strengths and perspectives to Ascential. Our employee-led groups and networks, Ascential Pride, Black in Business, EmPower: Ascential Women's network, Shalom Ascential, Christian Ascential and Latinx, help us to create a place where communities and allies can connect and share experiences. We are proud to have been recognised as a best performer in the FTSE Women Leaders Review for six consecutive years, listed in the Bloomberg Gender Equality Index and ranked highly in both MSCI and Sustainalytics ESG indexes.
We’re committed to ensuring we have a positive impact on the environment and communities in which we operate and we support our people to be more environmentally friendly, including ensuring our pension plan defaults to sustainable options.
We are committed to supporting charities with contributions, volunteer work and knowledge sharing. We have over a decade-long partnership with The Prince's Trust and sponsor initiatives to empower young women and support underserved communities
Recognising great performance is a key part of our culture. Our Awards schemes recognise and reward the brilliant achievements of our people.
We have a truly flexible working environment with a wide range of flexible, hybrid and agile-working arrangements. Conversations about flexible working have always been - and will continue to be - actively encouraged here.
Our benefits and wellbeing package offers flexible benefits you can tailor to your own personal needs, including:
- 25 days of holiday per year - with an option to buy/ sell upto 5 days
- Pension, Life Assurance and Income Protection
- Flexible benefits platform with options including Private Medical, Dental Insurance, Critical Illness and the Ascential Shares Scheme
- Employee assistance programme, season ticket loans and cycle to work scheme
- Volunteering opportunities and charitable giving options
- Great learning and development opportunities.
We want to ensure everyone has the opportunity to perform their best when interviewing, so if you require any reasonable adjustments that would make you more comfortable during the process, please let us know so that we can do our best to support you.
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