Financial Data Analyst

Описание

KEVIN NIAMKEY

DATA SCIENTIST | QUANTITATIVE ANALYST
Paris, France • +33 768 737 240 • kevin.niamkey@outlook.com
Data scientist and quantitative analyst with a proven track record of leading and supporting data mining, modeling, and
analytics projects, developing and maintaining complex data pipelines, and enabling data -dri ven organizations by drawing
on deep expertise in quantitative analysis, statistical analysis, and mathematical modeling.
• Skilled in utilizing data science tools and techniques to drive business intelligence and insights generation for financial markets .
• Excels in translating complex issues to data science problems, performing data analysis and modeling, and providing solutions .
• Highly experienced in collaborating closely with Data Analysts, Data Engineers, ML Engineers, and Product Managers.
• Applies AI, ML, advanced analytics, and visualization techniques to diverse datasets to deliver impactful business insights.
• Extensive knowledge and expertise in financial markets, including quantitative finance, commodities trading, and risk analysi s.

AREAS OF EXPERTISE

Data Science | Data Analysis | Data Modeling | Statistical Modeling | Statistical Analysis | Predictive Analytics | Quantitat ive Analysis |
Regression Analysis | Data Visualization | Machine Leaning (ML) | Artificial Intelligence (AI) | Natural Language Processing (NLP) |
Deep Learning | Data Mining & ETL | Data Wrangling & Cleaning | Business Intelligence | Financial Analysis | Risk Analysis |
Quantitative Finance | Cross -Functional Collaboration | Process Improveme nt | Project Management | Bilingual (English, French)

PROFESSIONAL EXPERIENCE
Back -Office Desk Analyst | Geax, Paris Aug 20 23 to Present
• Conduct detailed analysis of large volumes of financial data produced by companies listed on the stock exchange, identifying
trends, anomalies, and discrepancies and generating comprehensive reports to support financial decision -making.
• Work with cross -functional teams to streamline and automate back -office processes, improving the accuracy and efficiency of
financial analysis and reporting activities.
• Maintain clear, open communication with internal and external stakeholders to provide prompt responses to requests for
information and analytical insights, ensuring seamless operations and maximizing client satisfaction. Full -Time Study ( Master’s in AI and Specialized Master’s in Financial Strategies ) Aug 2021 to Aug 2023 Data Analyst | Data Scientist | Digitalis , Remote Aug 2019 to Aug 2021 • Drove the design and development of a business intelligence application (including data visualization interfaces and dashboards) using R and R Shiny to facilitate data -driven decision -making. • Utilized advanced statistical and data analysis techniques to build models that uncovered actionable insights from complex datasets and translated data findings into clear, concise visualizations on the application. • Collaborated with multidisciplinary teams to define project objectives, requirements, and KPIs for t he development of the
application, including effectively communicating complex technical concepts to non -technical stakeholders.
Data Scientist | Neuronix Consulting, Remote Jan 2018 to Jul 2019
• Designed an ML model in R, R Shiny, and Python using NLP techniques to analyze and classify the sentiment of commercial
service -related posts while using state -of-the -art algorithms and fine -tuned hyperparameters to optimize model performance.
• Gathered a diverse dat aset of commercial service -related social media posts and comments from various platforms and
performed data cleaning, text normalization, and feature engineering to prepare the data for sentiment analysis.
Data Analyst | Data Scientist | RCI Bank, Noisy -le-Grand, France Mar 2017 to Dec 2017
• Led the design and development of an ML model in R and Python that classified text and email responses from customer
satisfaction surveys into predefined categories to enable efficient sentiment analysis of customer responses.
• Integrated and processed multi -modal data from client satisfaction questionnaires while utilizing data ex traction and
transformation techniques to create a unified dataset for sentiment analysis.

Statistical Researcher | Rénass, Strasbourg, France Mar 2016 to Mar 2017
• Developed a robust statistical model in R to quantify and compare the differences between natural seismicity and seismicity
caused by human activity such as mining or hydraulic fracturing.
• Gathered seismic data, conducted extensive data cleaning to ensure data quality and compatibili ty for statistical analysis, and
employed statistical tests and ML techniques to identify patterns, correlations, and significant variations in seismic data.
EDUCATION

Specialized Master’s in Financial Strategies & Responsible Investments | Audencia Business School, Nantes, France (2023)
Coursework: Quantitative Finance, Stock Index Construction, Market Risk, Portfolio Risk, Value at Risk, Derivatives (Forwards, Swaps,
Futures, Options) , Green Finance
Master’s in Artificial Intelligence & Management | IA School, Boulogne -Billancourt, France (2022)
Coursework: Algorithms, Machine Learning ( Random Forest, Support Vector Machine, Xgboost ), Deep Learning (RNN, CNN,
Transfert Learning), Neural Networks
Master’s in Statistics | University of Strasbourg, Strasbourg, France (2015)
Coursework: Supervised & Unsupervised Classification (PCA, LDA, CAH, kmeans), Discrete & Continuous Probability, Linear
Modeling (Simple Linear Regression & Multiple Linear Regression)
Bachelor’s in Mathematics | University of Strasbourg, Strasbourg, France (2012)
Coursework: Fundamentals of Analysis (Usual Functions, Numerical Series, Integer Series), Fundamentals of Algebra (Complex
Numbers, Vector Spaces)
TECHNICAL EXPERTISE

R | R Visualization Packages (Shiny, Shinydashboard, Leaflet) | Python | SQL