Data Consultant - Milton Keynes
Aiimi Ltd, United Kingdom
Job Description
You will be part of a cross functional Data consulting team spanning data engineering, visualisation, analytics and science.
You will be working with our clients across multiple sectors, helping them to explore next generation data analytics and data
science techniques and tools to drive incremental business value from their data assets.
Previous experience of data science in an commercially focused environment and a passion for how information
(data and content) can be used to drive business value would be ideal for this role! You will have the opportunity to work
across four key data areas: Science, Engineering, Analytics and Visualisation and will be expected to specialise in one or
more of these areas.
This is a client facing role which will see you work on exciting client projects throughout the UK. Due to this, a willingness to
travel and working away from home are essential to this role.
Requirements
You will be responsible for collaborating with business subject matter experts to discover the information hidden in various
sources of content and data, helping our clients make smarter decisions to reduce service failure and deliver better
outcomes to their customer base. As you begin your role with Aiimi, your primary focus will be in applying data mining
techniques, statistical analysis, building high quality predictive algorithms and models, using machine learning techniques
to classify data and content, and build recommendation systems.
Your role will be involved in the following areas:
- Liaising with our clients so that their information can be used in context, be relevant and be easily consumed by those who need it
- Analysing and interpret patterns and trends
- Developing new and innovative ways of working in order to drive efficiencies in the business
- Creating new triggers and associated interventions to affect future outcomes
- Prove/disproving hypothesis and theories into facts and informed points of view
- Supporting strategic planning
- Fulfilling timely reporting requirements including dashboards and balanced scorecards
- Ensuring new models, reports and data architectures are promoted and published to centralised self-service data warehouses as required
- Data engineering, analysis and building machine learning models
You will be responsible for the following areas:
Data Science
- Building and optimizing classifiers using machine learning techniques
- Data mining and statistical analysis using state-of-the-art methods
- Creating automated anomaly/error detection systems
- Measuring the accuracy of predictive models and continually improving their performance
Data Analysis
- Profiling, cleansing, and verifying the quality of data used for analysis
- Identify patterns in data, working with the business to interpret meaning and associated business value
- Find ways of capturing insight from all appropriate internal and external sources of content and data
- Cost and benefits analysis, return on investment analysis, risk assessment, and business case development to support transformation
- Provide advice and support to answer queries, determine route cause analysis of issues, and support incidents and emergencies
- Provide support in collating information that is required for subject access requests, legal matters, customer requests,
- complaints, year book, regulation, business plans, performance reviews, budgets, and strategic programmes
Data Aquisition / Engineering
- Extending data with third party and publicly available source of information
- Identifying new data collection processes to include information that is relevant for building analytic systems
- Identifying root cause issues of poor data quality and working with data and content owners to identify new processes to remedy
- Find ways to extract data from content (classification and content analytics) so that it can be more easily analysed and integrated into other data sources
- Identify data quality issues, identify root cause, and initiative transformation to improve data capture and associated data quality
- Supply of data extracts for other colleague analysis requirements
Data Visualisation
- Presenting analytical results in a clear manner using visualisation tools
- Utilise user centred design methodologies to personalise and maximise end user experience Information strategies: data management, content management, business intelligence, mobile, collaboration/social, business process management/workflow, digital, employee, cus