We’re Indicia Worldwide. We are a data-led communications agency with global production reach and we create new value at every step of the journey for some of the world’s biggest brands.
Indicia Worldwide is the product of three successful businesses, brought together by our parent company Konica Minolta in 2017. The vision was, and is, to create new value across the remit of marketing for our clients.
How do we do that?
- By being more efficient – using data, technology and global production capabilities to deliver brands’ messages at scale and speed.
- And by being more effective – using data and human insights to create mutually rewarding experiences for consumers and brands.
We’re a global end-to-end marketing agency with more than 700 people, located all over the world. Our clients believe in what we do because our people love solving client problems. We’re agile, flexible, and fun to be around too!
People Working for Indicia Worldwide is fast-paced, rewarding and thought-provoking. Our people create new value for our clients. This is an inspiring purpose – and Indicia Worldwide people are an inspired bunch!

Summary:

Indicia Worldwide Analytics and the Data Science team focus on solving business problems through the use of data and insights. This multidisciplinary team delivers value through building analytics products that scale for our clients and partners.

The Data Scientist will take the charge of scoping and hands-on delivery of analytical solutions that help solve our client's problems. We see this role as a key enabler for helping our clients grow through better data-driven decision-making.

The Data Scientist will play a hands-on role to ensure we are meeting our client delivery expectations. The role will interface with many areas of the business including marketing, client services, production and print management, planning, creativity and technology, as well as building relationships with clients.

This is a great opportunity to join a growing, agile and fast-paced agency, where data is at the heart of its proposition.

Purpose of the role:

The Data Scientist will be responsible for ensuring robust analytical frameworks and methodologies are applied to solving business problems. The candidate will be adept at using data mining and science techniques to analyse large, structured, and unstructured data sets to find patterns and insights that will help improve business performance. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

The Data Scientist will also ensure technical requirements and specifications are translated to a non-technical audience and will often work alongside client services teams to deliver easily accessible client presentations.

Key Responsibilities:

• Work closely with the UK team, client managers and relevant stakeholders to deliver insightful analysis to our clients
• With senior support build and test machine learning models and frameworks
• Track and resolve risks, issues, and action items throughout the project lifecycle
• Ensuring quality and accuracy of analytics deliverables
• Work on data science components in product solutions we are developing.
• Review existing ML models or algorithms and work on efficiencies in existing approaches where appropriate
• Work with the DSA team on opportunities to improve the development and deployment of machine-learning models
• Work with client teams and senior members of DSA to produce client-ready presentations both technical and non-technical.

Key Experience, Skills and Knowledge:

 • A degree or equivalent in a numerical subject such as Data Science, Computer Science, Mathematics, or Engineering.
• Excellent communication skills, both written and verbal.
• An ability to present complex or highly technical issues in simple and easy-to-understand formats, for technical and non-technical audiences.
• Good data mining and manipulation techniques on both unstructured and structured data sources
• Good programming skills, with one or more programming languages such as R, Python, Java or SQL.
• Good knowledge of different statistical and machine learning concepts like clustering analysis, regression, random forest, gradient boosting, collaborative filtering, etc. And hand on experience in applying one or more techniques.
• Experience in commonly used data science and analytics platforms, such as AWS Sagemaker, Data Bricks, etc. or Databases and database tools, such as MySQL, Amazon Redshift, and Snowflake.
• Experience in using Version control tools, such as Git, GitHub and SVN.
• Self-starter with a proactive attitude and enthusiasm for data. The ability to collaborate as part of a team, but also work well independently.

We are an equal opportunities employer and will make any reasonable adjustments to accommodate the needs of all candidates. If you have any such needs or requirements in the context of your interview, please notify us so that we can make the appropriate arrangements.