Application Text - Senior Data Analyst

 Over the years I have worked for the CBRT, my job has involved an extensive focus on the real and financial sector analyses in financial stability and a macro-prudential policy-making framework. In this endeavour, my work has been a crucial source of contribution in supporting the policymakers. My past and current work schemes have required a considerable extent of analytical skills, which have proved to be vital in the achievements of my practical experience as well as my theoretical work.

My particular work scheme in the CBRT has always involved a very heavy workload spread all around the year constrained by very strict deadlines and by very tight time budgets, all quite challenging. I have learned through the years how to manage these constraints and transform the stress and uncertainty along with it into productivity rather successfully by being highly organized and thorough meticulous planning. I have had longer than 10 years of experience in leading project teams successfully. I have also had inter-organizational experience in data management issues both within the country and abroad in meeting and/or co-working levels. As to statistics and data issues, I can comfortably say that the heavy workload I carried through these years involved dealing with very large datasets, processing them, and turning them into information for policymaking.

Currently, I am working as a research analyst in the Structural Economic Research Department of CBRT, and as a seasoned expert in real sector analysis, risk, and banking. My current responsibilities involve the coordination of the establishment and the development of research and reporting data warehouses. I am also responsible for preparing ad-hoc reports and research notes and papers for the upper management regarding the credit and systemic risks of real and financial sector firms, as well as the financial stability and economic development issues. I have also been responsible for editorial issues related to the CBRT’s online publication Central Bank Review hosted by Elsevier, for about a year. Recently, I have applied for an in-house tutor/trainer role and I hope to train the next generation colleagues in mostly data analysis and reporting issues.

For all the years I have worked at the CBRT, my job has always required meticulous work in managing the data. My approach to data, in general, is to put an effort to acknowledge the possible uses of the data in question, at first, if I have a first-time encounter with it rather than catering to it myself to fill a need. This usually, essentially means a reasonably deep mental focus on the whole process for me, involving all the details from the collection to possible outcomes/end products. If the need for data arises from an end-product or a prospective design then I look for the raw data, possible sources for it, and for ways of obtaining the most optimal way of collecting the cleanest data as quickly as possible. Further, I try to imagine the data processes, draw simple flowcharts, and write the pseudocodes as much as I can if possible.

The datasets I’ve worked on in particular have included the credit/loan data, bank financials, and individual real sector firm financials. Those datasets are mostly very granular and complex if not highly frequent (from daily to annual), and very large given the number of individual unique IDs and spanning a range of 15-20 years depending on the datasets. As detailed in my CV, my work has encapsulated all ranges of subprocesses including the data collection to the production of final reports published, ensuring high quality in the data in terms of integrity, validity, and accuracy at all times as much as possible.
During the years I’ve worked, at the Statistics Department particularly, I’ve either managed project teams as well as task groups or I’ve individually run projects which I independently designed. Those projects and tasks themselves involved extensive use of analysis and reporting applications (e.g. SAS, Business Objects, Oracle BI, sometimes Excel and VBA) which I also employed to carry out a considerable amount of work. I also have used statistical and mathematical analytic methods, especially in both project designs and in preparing report templates. I further employed data mining and machine learning methods both for data analysis, pattern recognition, and rule learning although not extensively. Also worth mentioning, I have designed numerous interactive and dynamic data forms, and reports as well as a web-based reporting platform using SAS, Business Objects, Oracle BI, VBA, and QlikView, and helped the crew maintain CBRT’s Electronic Data Delivery System (https://evds2.tcmb.gov.tr/index.php?), in the absence of now available data analysis and visualization tools like Tableau and MS Power BI.