Purpose of the role :
The Head of Analytics and Data Science will be responsible for driving analytics innovation and best practise for Indicia Worldwide and our clients.
The role will focus on realising the strategy and ensuring client deliverables are met to standard and on time.
The Head of Analytics and Data Science will be pivotal in building and mentoring a successful commercially focused analytics team.
The role will utilise analytical and machine learning techniques to deliver data driven solutions to our clients. The Head of Analytics and Data Science will be responsible for the full analytics and data science lifecycle, from problem identification to model deployment and operations .
Key Responsibilities :
Lead the Analytics and Data Science team which delivers Insight and Machine Learning capabilities to provide strategic actionable insight and data products to drive growth for our clients
Develop strategies, operating models, roadmaps and business cases for data science and analytics applications
Lead the relationship between stakeholders and team members and the full end to end project delivery, which includes, business requirements, planning, design, development and implementation of Data Science and Analytics projects.
Work closely with client managers and relevant stakeholders to deliver insightful analysis to our clients
Establish and maintain end to end data quality framework to ensure data assets and models are accurate and comply with high quality data standards
Track and resolve risks, issues, and action items throughout project lifecycle
play a key role in defining, building and managing the data science and analytics platform that enables the end to end development of analytics, insights, data mining and machine learning
Problem-solve with product and client teams, advise on how to leverage data science across the company and for our clients
Help guide the development of our internal analytics and data science products.
Work with lead data scientists to develop technical solutions, frameworks and methodologies to solve key business problems and challenges
Key Experience, Skills and Knowledge :
A degree or equivalent in a numerical subject such as Data Science, Computer Science, Mathematics, Engineering
Knowledge of commonly used data science and analytics platforms, such as AWS Sagemaker, Data Bricks etc
Familiar with common data science frameworks such as Spark MLib, TensorFlow, Keras etc
Experience of using one or more programming languages, R, Python, Scala, Java and SQL.
Experience of leading a team that have delivered Machine learning outputs and knowledge of techniques like random forest, gradient boosting, collaborative filtering etc
Experience managing the end to end analytics and machine learning lifecycle
A collaborative leader with strategic acumen and problem-solving skills, able to inspire and motivate colleagues as well as work alongside them as required
Demonstrable creativity and a commitment to future-proofing service and delivery in a fast paced, ever-changing environment
A forward-thinking individual with good knowledge of products and services available (vendors and technology) to help maximise the value possible through the combination of technology with data science
Excellent communication skills, both written and verbal. Ability to present complex or highly technical issues in simple and easy-to-understand formats, for technical and nontechnical audiences
Ability to build strong relationships and influence decisions with internal and external stakeholders at all levels
A good understanding of agile product development and software development lifecycle
An ability to think and plan strategically
We are an equal opportunities employer and as such, 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.