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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