Within the data services team, I provide data engineering support of user-visible systems in a test-driven manner. The team is constantly researching new technology developments that can be implemented in our systems to drive internal innovation.

• Implement multiple combined backend/frontend data systems, storing data to multiple locations (datalake, data warehouse, etc) and exposing it through APIs, allowing business units to capitalize on exposed knowledge.
• Gave feedback/insight on potential customer data usage based on experience in PhD, influencing data architecture and cutting project times while increasing client satisfaction.
• Manage communication between developers, product owners, and clients to ensure expectations matched delivered software. Frameworks used:
• Airflow
• ArgoCD
• AWS
• CircleCI
• Docker
• Git
• Kafka
• Kubernetes
• PostGres
• Python
• Unix

I provide data science support to the DataLab branch of enpact, where we attempt to use data-driven approaches, combining governmental and first-hand data to inform and advise policy-makers on improving entrepreneurial outcomes in developing countries. This data is reflected by the Startup Friendliness Index. I examine the existing database and devise methods to improve indicator quality (in terms of automated extraction capability, accuracy, and representative-ness) by identifying the core message of each indicator, locating alternative measures, and automating the extraction of useful data. As a result, team resources have been diverted from manually retrieving and cleaning data and additional data and geographies can be easily supported. Responsibilities include:

• WebScraping and API access of key data points
• Automating data collection and reducing manual workloads
• Consulting on improving data quality
• Deploying an SQL database to provide data for the interactive website

Frameworks used:

• Python (pandas, beautifulsoup, requests, sql-alchemy, selenium)
• SQL (PostGreSQL)
• Git (GitLab)
• Office (Excel, Word)

I conducted basic research in Auditory Neuroscience in an animal model using electrophysiology. While my core project is described below, I also acted as lab manager, planned/performed ancillary experiments as requested by my supervisor, and provided technical support to colleagues and junior researchers. I also attended conferences to relay my results to both experts and laymen around the world. Responsibilities included:

• Programming software/hardware to enable neural data collection
• Planning and conducting electrophysiological experiments
• Cleaning and analysing data
• Programmed software to assist in the process
• Designed software in a robust way using GUI input and error-detection to allow non-technical users to benefit from the software
• Performing inferential statistical analysis with some exploration of:
• Generalized linear mixed models
• Principle Component Analysis
• Classification Learning
• Write and visualize results for communication through posters, talks, and journal articles
• Manage projects and maintain collaborations with other research groups

Frameworks used:

• Matlab (Statistics, Wavelet, Curve fitting packages)
• Python (Scipy)
• R
• Git (GitLab)
• LabView
• RPvdsEx
• Office (Excel, Word, Powerpoint)
• LaTex

Specialised Analysis methods include:

• Time-series/frequency analysis
• Wavelet Analysis
• Poisson-based event detection
• Peak detection
• Multivariate feature extraction
• Nonlinear Regression Modelling and curve fitting

I designed jigs, stands, tables, and various tooling by modeling with SolidEdge, improvising, and incrementally improving past designs in order to facilitate quality and quantity of work created on all production lines. I performed calculations pertaining to solid mechanics, welds, and cost effectiveness in order to assist and cross-check design work by co-workers and myself. I managed production line lay-outs on AutoCAD and co-ordinated meetings between several departments in order to strengthen team communication involving trouble-shooting, process implementation, and incremental design improvements. I created various documents, including an Engineering Technical Report, by investigating physical circumstances and consulting hand-books in order to deliver information and specifications to company clients, vendors, and inspectors

Frameworks used:

• SolidEdge
• AutoCAD
• Office (Excel, Word, Powerpoint)

Specialised Analysis methods include:

Many M.Sc. and PhD students in the lifesciences struggle with adapting to the programmatic demands of modern science. I hold regular workshops where we explore datasets collected by participants in a case-study format and examine the methods available to clean, preprocess, analyse, and visualize data.

Frameworks used:

• Python
• R
• Julia
• Ubuntu
• Jupyter

Together with other elected representatives, we formed a council representing the PhD students to the faculty and Board of Directors.

Responsibilites included:

• organizing events such as social Barbecues, scientific/transferable skill workshops, and student-run conferences under a modest budget
• Attend Executive Board of Director Meetings to keep on top of institute direction and represent PhD student interests
• Participate at meetings of PhD reps in the Leibniz Network for larger organizational direction
• Assist students in disputes with faculty
• In particular, the organization of a guiding constitution for PhD rep behaviour and governance.