SOGBOE Odette

AI Engineer

https://www.opentalent.in/sogboe-odette

AI Engineer with less than a year in ML pipelines, fintech, and data-driven solutions.

Key Strengths

Demonstrated ability to build end-to-end ML pipelines, including EDA, feature engineering, and model deployment, as shown in the Credit Card Fraud Detection project.
Experience with key ML/AI libraries and tools such as XGBoost, SHAP, Pandas, NumPy, and Streamlit.
Proficiency in Python, a core language for AI/ML development.
Exposure to fintech concepts and API integrations (Flooz, T-Money) relevant for real-world applications.
Strong foundational understanding of database management (PostgreSQL, MySQL, SQL) and OOP principles (Java).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio demonstrates a blend of academic rigor (Credit Card Fraud Detection, Travel Management Application, Student Data Management System) and personal initiative with real-world applicability (TogoEpargne — Fintech Concept). This diversity, coupled with a stated interest in fintech and measurable, real-world impact, suggests a proactive and results-oriented individual. The leadership role in a tech club indicates a willingness to contribute to a community and foster learning, which can be a positive cultural fit. However, the lack of professional experience means cultural fit is primarily inferred from academic and personal projects.

Soft Skills & Operational Fit

The candidate highlights analytical, detail-oriented, autonomous, team collaborator, and clear communicator soft skills. These align well with the demands of an AI Engineer role, which often requires independent problem-solving, meticulous data handling, and effective communication of complex technical concepts. The leadership role as Vice-President of the Tech Campus Club also suggests organizational and collaborative abilities.

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Projects

Credit Card Fraud Detection

January 1, 2026 – Present

Full ML pipeline on 284k-transaction ULB dataset (0.17% fraud rate) with AUC-ROC 0.9779. SHAP analysis identified V14 & V4 as top fraud predictors; 30-page LaTeX report + 9 figures. Deployed interactive Streamlit dashboard for stakeholder presentation.

Travel Management Application

January 1, 2026 – Present

Built full OOP application modelling customers, trips & bookings using inheritance and encapsulation.

TogoEpargne — Fintech Concept

January 1, 2026 – Present

Digital platform to formalise tontine savings in Togo with BCEAO-compliant architecture. Integrated Flooz & T-Money APIs; produced institutional pitch deck for partner outreach.

Student Data Management System

January 1, 2026 – Present

Designed normalised relational schema; wrote complex queries (joins, aggregations, subqueries). Delivered reporting layer for academic administration.

Key Strengths

Demonstrated ability to build end-to-end ML pipelines, including EDA, feature engineering, and model deployment, as shown in the Credit Card Fraud Detection project.
Experience with key ML/AI libraries and tools such as XGBoost, SHAP, Pandas, NumPy, and Streamlit.
Proficiency in Python, a core language for AI/ML development.
Exposure to fintech concepts and API integrations (Flooz, T-Money) relevant for real-world applications.
Strong foundational understanding of database management (PostgreSQL, MySQL, SQL) and OOP principles (Java).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

SOGBOE Odette

Key Strengths

Cultural & Operational Fit

About

Top Skills

Skills

Education

Projects

Key Strengths

Cultural & Operational Fit