o
omosea_1

Success A

@omosea_1
5,0(1)

Quantitative Developer, Financial Engineering, Algorithmic Trading, Python

Nigeria
Inglese, Francese, Spagnolo, Tedesco, Italiano
Alcune informazioni sono riportate in lingua inglese.
Chi sono
I am a Quantitative Developer specializing in financial engineering, algorithmic trading, and advanced Python solutions. I build robust quantitative models, back-testing systems, portfolio optimization frameworks, derivatives pricing models, risk analytics, and financial forecasting tools. I focus on delivering accurate, scalable, and production-ready solutions that help businesses, traders, researchers, and financial institutions make data-driven investment decisions.... Continua a leggere

Competenze

o
omosea_1
Success A
offline • 
Tempo di risposta medio: 3 ore

Consulta i miei servizi

Efficienza di business e automazioni
I will perform portfolio optimization and risk analysis
5,0(1)
Integrazioni IA
I will build custom ai agents and automate your business workflows

Portfolio

Esperienza lavorativa

AlgoSmith

Algorithmic Trading Developer

AlgoSmith • Freelance

Jun 2026 - Present1 mo

Designed and implemented algorithmic trading strategies using Python, quantitative analysis, and machine learning approaches. Developed automated trading models based on historical market data, technical indicators, statistical signals, and time series analysis. Conducted backtesting and performance evaluation to measure strategy profitability, volatility, drawdowns, and risk-adjusted returns. Built research frameworks for analyzing market patterns, forecasting price movements, and identifying trading opportunities. Applied statistical methods and machine learning algorithms to improve predictive performance and strategy robustness. Created automated data pipelines for collecting, cleaning, and analyzing financial market information. Achievement: Developed systematic trading solutions that enhanced strategy testing, improved decision-making processes, and provided reliable quantitative insights for financial market analysis.

AIR™️

Machine Learning Finance Specialist

AIR™️

May 2026 - Present2 mos

Developed machine learning solutions for financial analysis, forecasting, and risk assessment. Built predictive models using Python, supervised learning algorithms, and financial datasets. Applied feature engineering and model optimization techniques to improve predictive accuracy. Integrated machine learning with traditional financial analysis methods to create advanced analytics solutions for market prediction, portfolio evaluation, and risk monitoring. Achievement: Successfully implemented AI-powered financial models that enhanced forecasting capabilities and improved analytical decision-making.

FinancialHedge

Portfolio Risk Management Analyst

FinancialHedge • Part time

Jul 2026 - Jul 20260 mos

Designed portfolio risk analytics solutions using quantitative methods, Python programming, and financial modeling. Developed frameworks for measuring portfolio volatility, downside risk, and performance under different market scenarios. Created risk assessment tools using Monte Carlo simulation, stress testing, and statistical analysis. Evaluated portfolio diversification, asset relationships, and potential loss scenarios. Achievement: Delivered risk management systems that improved portfolio visibility and supported stronger investment strategies.

1 Recensioni
5,0

(1)
(0)
(0)
(0)
(0)
Valutazione dettagliata
  • Livello di comunicazione del venditore
    5
  • Qualità della consegna
    5
  • Valore della consegna
    5
1-1 di 1 recensioni
Ordina per
Più rilevante
    R

    roor_90

    Cliente abituale

    US

    Stati Uniti

    5

    Thank you so much. I truly appreciate your professionalism and the quality of your work. Your attention to detail and clear communication have made this process much easier. I’m grateful for your support and look forward to continuing to work with you.

    50 USD-100 USD

    $

    4 giorni

    Tempo

    gig

    Efficienza di business e automazioni

    Utile?
    No