Curriculum Vitae
|Mostafa Kateb Nejab |∗ London |
| |8 kmostafa89@ |
| |: kmostafa89 |
| |: |
|Personal |Data Analyst aspiring to be a data scientist,currently specialising in modelling, visualisation and machine learning. I hold |
|Statement |numerous technical proficiencies and I am also a First-Class Honours BSc graduate of Actuarial Mathematics and Statistics. My |
| |technical aptitude has allowed me to successfully develop business functions to support enhanced operational efficiencies and |
| |productivity. |
| | |
| |My communication skills provide me with the foundation to create and maintain strong professional relationships with colleagues and|
| |clients alike. I am accustomed to working on numerous work streams simultaneously and can schedule tasks in accordance with their |
| |priority and designated timescales. My interpersonal skills allow me to adapt easily to new working environments. I collaborate |
| |effectively within a team, whilst maintaining the self-discipline to deliver independently. |
| | |
|Key Skills |Data Analysis |Data Modelling |Data Visualisation |
| |Machine Learning |Financial Services |Actuarial Mathematics |
| |Statistics |Report Production |Forecasting |
| |Coding |Client Relations |Communications |
| |Business Development |Organisation |Presentations |
| | |
|Technical Proficiencies |Python |Pydata |Sqlite |
| |Computer Vision |Microsoft Excel |Microsoft SQL Server |
| |Pandas |Numpy |Scikit Learn |
| |Matplotlib |Bokeh |Regular Expression |
| |HTML |CSS |JavaScript |
| |MySQL |Linux VPS | |
| | |
|Qualifications |BSc: Actuarial Mathematics and Statistics (1st) Kingston University |
| |Modules Included: |
| |Optimization |
| |Partial Differential Equations |
| | |
| |Time Series |
| |Mathematical Programming |
| | |
| |Contingencies |
| |Further Inferences and Bayesian Methods |
| | |
| | |
| |A Levels: 4 Qualifications London Academy |
| | |
| |GCSE’s: 4 Qualifications graded A* to C Hendon Tuition Centre |
| | |
|Training |Neural Networks and Deep Learning |
| | |
| |Munich Re Data Analyst May 2019 to -Pres |
| | |
|Professional Experience |Utilising data between the Actuarial team and the Underwriters in order to monitor and update the reserves requires for the current|
| |business need, this was done by creating a unique report for each class of the business where the received premiums and paid |
| |claims, outstanding claims and Incurred but not reported claims for that class was recorded in a triangular format also knows as |
| |the triangles. |
| |Regulatory Audit report for the Lloyds of London |
| |Maintaining and updating SQL server for the Reserving database, including creating Stored Procedures, Custom Views, and functions |
| |to make the required data easily accessible within the Reserving team. |
| |Intensive use of Macros, VBA Active x Data object for connection to and from SQL Server and MS Access, to filter data, import |
| |filters data into Excel and export the modified version back into the SQL data warehouse. |
| |Generating Python scripts to run SQL queries and/or Excel Macros in a single script to automate the process even more. |
| |Generating and maintaining KPI reports for the business such as various Claims model, namely various types of claims such as |
| |attrition, large and catastrophic claim and the Premiums received in order to visualise the total loss and gains of the business |
| |under various categories. |
| |Assistance in Server-side production and allocations of the existing data for the |
| |IFRS17 |
| |Premiums and Claims allocation from class to sub class of the business using existing data, I achieved this using Python Pandas |
| |library by creating a matrix of premiums/claims ratio for the existing class, and allocating the classes to sub classes using the |
| |ratio matrix. |
| |Web scraping data from the net to assist the underwriters and actuaries in their modelling in areas such as War and terrorism |
| |categories. |
| |Migration of MS access to SQL sever and creating new Views in SQL server to replace the queries in access, and new stored |
| |procedures to replace the macros. |
| |Data Analyst – Iplato Healthcare Sep 2018 to Nov 2018 |
| |Analysing the output of data from the “myGP” application and producing reports on the results |
| |Providing expert business support to develop this new start-up company |
| |Recommending means to utilise data analytics in an operational environment and how this could support and develop business |
| |intelligence and growth |
| |Maintaining the application to ensure it was running at optimal levels |
| |Creating data visualisation dashboards and automated campaign reports |
| |Developing robust and bespoke data sophistication queries to extradite patient and GP practice information |
| |Establishing strong lines of communications with external data suppliers |
| |Ensuring all process and information flows were running efficiently and effectively |
| |Facilitating data extraction techniques using Python, MySQL and SSH connection |
| | |
| |Data Analyst - National Air Traffic Services (NATS) Dec 2017 to May 2018 |
| |Conducting intricate analysis of airspace, airport and flight data and radar information to support the efficiencies of Air Traffic|
| |Controllers to monitor airspace |
| |Creating dashboards for flight delays and danger areas designed to mitigate delays, efficiently use fuel and utilise the available |
| |air space |
| |Producing forecasts using regression and classification methods in machine learning and ensuring the accuracy of all information |
| |provided |
| |Developing means to automate existing reports to enhance the reporting functions reliability, accuracy and speed |
| |Conducting data analysis and data visualisation |
| |Processing statistics |
| |Making sure the dashboard and interactive charts created were simplified for the client’s daily use, and could be easily deployed |
| |onto the server |
| |Creating structed data from unstructured data arrays and online resources |
| |Extracting vital data from junk and unstructured data |
| |Facilitating technical data presentations in a manner that could be understood by non-technical personnel |
| |Identifying and communicating solutions to business issues by justifying machine learning models, and extracting and visualising |
| |the contribution of data features |
| |Ensuring the data was aligned to the business expectations and suggesting solutions to achieve this |
| |Building pipelines to transfer and cleanse data from one platform to another |
| | |
| |Achievements |
| |Successfully achieved 95% accuracy in Machine Learning Modelling through utilising Python skills and knowledge |
| |Created a module that was used to predict 3di-scores, five years into the future, based on two years of historical flight data |
| |which achieved 95% accuracy with the root mean squared error 1.05 |
| |Dramatically reduced manual duties by months through automating reports and tasks |
| |Consistently exceeded 85% forecasting accuracy, using regression and classification methods in Machine Learning |
| | |
| |Risk Reporting Analyst – BGC Partners Feb 2017 to Mar 2017 |
| |Creating daily credit reports which outlined the unsettled trades and escalated the credit team levels to the traders |
| |Adjusting trading prices by using the Bloomberg terminal to conduct the final calculations of counterparties exposure |
| |Producing risk calculations and risk reporting |
| | |
| |Research Executive – TNS May 2015 to Feb 2017 |
| |Managing the daily operations of the production department and ensuring the number of samples produced were in accordance with the |
| |targets and client specifications |
| |Conducting intricate analysis and cleansing of project data |
| |Producing suspicious data reports and escalating to the operations centre |
| |Translating technical and mathematical data into presentations for non-technical stakeholders to determine the future of projects |
| |Creating periodic project reports for clients |
| |Identifying and implementing means to enhance efficiencies and productivity through automating reports |
| |Creating connections between SQL and Excel |
| |Providing the expert function for string, dates, functions, left-right and fuller joins, temp-tables, pivot tables, sub-queries, |
| |ADODB, Outlook outward, files and folder manipulation and scripting within T-SQL and VBA |
| |Establishing strong client professional relationships |
| | |
| |Achievements |
| |Migration from MS access to SQL server, with the new views and stored procedures to replace the queries and macros in MS access. |
| |Saving company 1000s of hours through automation and maintaining the automated systems. |
| |Passing technical knowledge to fellow team members who are less technical through one on one tutorials or groups presentations. |
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