Tomas Jasaitis

Creating data science platform.

Product summary:

• Data enrichement - using NLP machine learning techniques to enrich healtcare data.
• Data extraction - using deep learning techniques to extract data from documents.
• Healthcare knowledge graph - matching buyer and supplier needs.
• Anomaly predictions - identifying trends and anomalies in contracts.
• Matching engine
• Discovery engine

Website analytics - data architecture for entire website usage tracking and converting in more human readable format for everyone to use. Standardised tracking across different tracking products to create clear and scalable approach on gathering data for data driven decision making. This allows teams and individual product teams to better understand successes and learn from failures. Achieved by incorporating all data to single source of truth. It combined all data across different sources and platforms like email campaigns, mobile applications, third party website analytics tracking and others. All this was done to have a single point of view of user experience and actions taken to help user to achieve what they came to site to do. This helps to improve knowledge sharing between teams and for data science team to analyse and build smart products and current product improvements.

Data science products - created reporting product for charities to gain insights on how they are doing on JustGiving platform. It consists of over 150 metrics and quarterly amount raised predictions with recommendations on how to improve their performance on a platform. Consists of metrics from simple transactional stats to user retention, segmentation to graph growth metrics and other. Work involved working with devs to set up CI (continuous integration) pipelines, different environments, microservices, autoscaling groups, front enders for design and dashboarding to complete the project.

Fraud predictions - product used to identify crowdfunding pages that potentially are fraudulent for further manual investigation.

Graph analytics – building network graphs to better understand the connectivity between the people, content and causes. Using findings to improve product experience. Built a causes reach to show the impact of individual causes and their reach to better understand user’s behaviour and used it to build metrics and visualisations as a report to improve product adoption. Email campaigns tailored for individual users with more relative content and content recommendation based on analyses findings. Products build: charity reach on platform, for charities to gain insight on how big giving network is and how to best communicate with their network.

Hackathons - won internal hackathon by creating generosity score based on pagerank, to show generosity score of users to encourage gamification on JustGiving site. Other hackathon project involved fundraiser insights dashboard that involved page view predictions, friends to notify and mediums to use to increase fundraiser network reach and gain more page views.

Measure/analytics – improving business KPI’s to incorporate business strategy changes. Acquisition models to understand traffic sources and their importance to the user to better strategize user acquisition. Social media sharing tracking to graph models to understand user acquisition and conversion.

Hook based analyses to engage and retain user on the site. Identifying user triggers their actions that lead to reward and future investment.

CTR/funnel measures to sequence based analyses to identify and act upon user’s experience in a wanted business funnel, also identifying steps to improve conversion and optimise it.

Product summary:

• Website analytics - internal tracking solution build, analytics front end solution, metrics and KPI's for business build, self-service solution for analysts and PM's
• Fraud predictions - predicting frodulent pages
• Give graph - social network graph
• Manement team KPI's - C level analytics for data driven decision making
• Email campaigns - social graph based email campaigns
• Data science - automation services for data extraction and wrangling
• Data science - analyses service solution - automated analyses and data for products creation running over 2.1mln queries a month

Developed activity reports, for the first time in a company history, to provide a clear visibility of business clients activity across different disciplines, brands, regions and continents. Reports provide valuable insights in operational activities. Data insights allow to plan meetings better with clients and to represent different brands of Page Group. Started working with different departments (Marketing, Accounts, Finance and others) in an organisation to allow to make smarter decisions using analytics, to make decisions on facts not opinion. Thus bringing Business Intelligence to front house.

Main responsibilities:

• KPI reports (weekly/monthly/yearly) - this role involves creating new KPI reports for business (gathering business requirements, writing requirements specifications, creating data models, report authoring) as well as automating current reports and data checks to facilitate increasing key performance indicators due to evolving business needs.
• Ad Hoc reports – writing SQL queries and presenting insights using MS Excel pivot tables and VBA to facilitate fastest delivery of a report. Choosing report delivery tool on case by case requirements analysis. Report delivery tools vary from Excel spreadsheets, Profile 7 saved lists, Crystal reports and IBM Cognos applications.
• Projects - Business Intelligence reports, identifying and coding records, new software testing and roll-out, system upgrades. Back office project/migration project – I was responsible for validating, amending and writing project plan scripts. Distributing cleansing tasks to colleagues.
• Data Warehouse - improving current databases (live snapshots and analytical databases) by reviewing scheduled tasks, SSIS packages, data and view loads, stored procedures, triggers and system logs.

Module assistant for Key Business Competences and Skills for placement search modules. Main responsibility was to help lecturer during the seminars and lectures. Other duties involved marking first and second years students weekly assignments, assisting lecturer with the preparation for the lecture and seminars. Basic administrative responsibilities. Collecting and analysing module feedback forms and presenting findings to the lecturer. Allocating students to the seminar leaders, tests and exams. Booking rooms for the exams, tests and extra classes. Communicating with students and helping them to improve their knowledge on how to use MS Excel.

Run seminars of student groups 5 to 30. Present main subject of the lecture and showing students how to apply theoretical knowledge.

Helped students.