Ana Clarke

• Manage projects life cycle to be completed on time, within the budget and scope implementing Agile, Waterfall or a hybrid of PM methodologies.
• Identify, plan, and communicate project risks and roadblocks to the project team.
• Develop solutions that balance cost, resourcing timeline, likelihood of success, and analytics risk.
• Preparation of SoW, project proposals and project artifacts, including funding applications for government agencies and other funders.
• Writing reports of the project’s status, including financial information.
• Provide leadership for project team by building and motivating team members to meet project goals, adhering to their responsibilities and project milestones.
• Assist the accounting and HR teams to reconcile resources spent in the projects and invoicing to clients.
• Training junior staff and assisting with their recruitment.

• Identify data analytics problems that lead to innovative solutions.
• Manage projects across multiple business units.
• Manipulate structured and unstructured data, address data quality concerns, data munging, and understand metadata for use in analysis.
• Build and deploy supervised and unsupervised machine learning algorithms.
• Model text data and build text classification algorithms using a range of NLP techniques.
• Communicate analysis results using easily understandable language and visualisation.
• Research and implement the application of new methodologies and ensure continuous improvement. 

• Managing and delivering analytical modelling outcomes for clients.
• Working on a full range of datasets and analytics projects; including customer segmentation and behavioural modelling, marketing optimisation, sentiment analysis, credit risk, fraud prediction, geospatial data analysis, and many others.
• Supervised and unsupervised machine learning.
• Managing and mentoring junior consultants.

Manage complex datasets to work on different end-to-end projects, such as:

• Build a model to predict the reliability of equipment.
• Prediction of the behaviour of online readers
• Modelling to forecast inventory demand based on sales data history in the factory field
• Correlation modelling to link data collected on the platform with off-platform data in the education sector to identify patterns and relationships between the characteristics of learners and learner outcomes.
• Modelling Big Data stored in Apache Spark.
• Running scalable data analytics on the cloud.
• Develop Machine and Deep Learning Algorithms. 

• Create and manage a multi-disciplinary research team from scratch.
• Define and implement research methodologies and data strategy in the project.
• Define the measurement framework and the team KPIs alongside the seniors researchers.
• Drive and encourage research initiatives.
• Provide consulting services for businesses and government in data science to understand key drivers of innovation success in business and how to translate this into actionable insights or data platforms for the business to implement and drive ongoing success.
• Deliver lectures, seminars, tutorials and workshops at undergraduate and graduate levels.
• Mentoring and coaching of research students, PhD candidates and fellows.
• Generate and implement a development career plan for the research team.
• Prepare budget and cost/benefit analysis.
• Publish research findings.