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Experienced and passionate data scientist, analyst and statistician with an academic background in mathematics and actuarial science.

Modules covered: Financial Mathematics, Survival Models, Actuarial Mathematics, Economics (Macro and Microeconomics), Statistical Methods in Insurance, Stochastic Processes and Accounting.

Relevant projects: MSc dissertation “Mortality modelling and projection” – Studying stochastic models for human mortality and finding best model for each selected country.

Relevant software packages: R (Extensive use throughout the year and when working on the dissertation).


University of Southampton

Data Scientist

Kat Pasecnika

Virgin Media

Championing the application of data to drive thought and influence strategic decisions. I am working and have worked on multiple research pieces that are of high priority to the business such as :
• Building the most optional customer contact strategy that increases making optimal meaningful contact with a customer at the right time which results in an increase of sales.
• Building a view of a customer's journey and identifying trigger points within that journey to design preventative measures for churn.
Other things I am passionate about as part of my role:
• Collaboration and building relationships across the business and  other data teams by organising Monthly Analyst Meetings within the department.
• Education of other non-technical members of the business on  Data Science by hosting a regular Data Science Catch-ups.
• Exploration of new tools and techniques that have potential to be beneficial in delivering Data Science projects more efficiently. - Successfully brought tools like Knime and Memgraph (graph database) into the team.

As a highly customer focused analyst, my main areas of focus were:
• Running investigations into performance/drivers/variances and customer profiling by using techniques such as regression and cluster analysis.
• Predicting future performance of the campaigns based on past performance by using techniques such as regression and random forest and decision trees in general.
• Producing summary statistics on trading impact, rationale and commentary for departmental activities and recommending course correction actions.
• Providing an assessment of value added/lost across the base each month and contribution of CVM activities.

British Gas

Customer Value Management (CVM) Analyst

Working at Thatcham Research, my role included :
• Analysing the latest trends in motor claims and repairs, and continuous development of statistical models and forecasts/predictions to analyse the risks of autonomous vehicle technology. Modelling approaches mainly including GLM, Decision Trees, Random Forest and Bayesian, with an ever-increasing variety of techniques used.
• Continuously researching and applying Bayesian Statistics (Multilevel modelling using Markov chain Monte Carlo simulations)
• Analysing and manipulating Big data.
• Working and sourcing statistical data for a variety of articles on the subject of autonomous driving and any driving related topics as part of BAU tasks.


Thatcham Research

Analyst/Statistician

As a young analyst at Ericsson I would enjoy:

• Data and performance analytics.
• Preparing KPI and SLA performance figures for the business and the customer.
• Developing new performance indicators and insights for the business in order to help see broader pictures of project performance.


Ericsson

Performance Analyst

I thoroughly enjoyed this short but valuable experience, as I took part in completely different activities to anything I have experienced before, mainly :
• Using various appraisal techniques for property development, project appraisals and evaluations.
• Assisting stakeholders with decision making on projects. 

Kat Pasecnika’s posts