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Job Details

Goodman Masson logo
Recruitment Agencies

Systematic Portfolio Manager

at Goodman Masson

ExperiencedNo visa sponsorship

Posted 17 days ago

No clicks

Systematic Portfolio Manager to relocate to Muscat, Oman to run and systematize multiple live sub-portfolios within three months, developing, testing and deploying quant-driven investment systems. You will build production-quality Python codebases, apply econometrics and machine learning (including RF and XGBoost), manage model risk and oversee multi-system, multi-regime strategies while working closely with the CIO. The role also includes production deployment, stakeholder communication, digital distribution management and partnering with Sales, Marketing and Compliance.

Compensation
Not specified

Currency: Not specified

City
Muscat
Country
Oman

Full Job Description

Systematic Portfolio Manager – Relocation to Oman

Location: Muscat, Oman

Employer: Growing Investment Management Firm

We’re seeking a talented Systematic Portfolio Manager, who is open to relocating to Oman to join a rapidly expanding investment management firm. This is a high-impact role for someone who wants real ownership, fast responsibility, and the opportunity to build and run systematic portfolios in a dynamic, entrepreneurial environment.

Role Overview

As a Systematic Portfolio Manager, you will take immediate responsibility for several live sub-portfolios, transitioning them to fully systematic oversight within the first three months. You will lead research, development, deployment, and ongoing management of data-driven investment systems, working closely with the CIO and broader investment team.

Key Responsibilities

  • Take over and systematize multiple existing sub-portfolios within 3 months, including signal integration, risk controls, and performance analytics.

     

  • Lead full-cycle development of quantimental investment systems-from hypothesis and empirical testing to production deployment.

     

  • Build modular, production-quality Python codebases using modern analytics, ML, and statistical tools.

     

  • Conduct research across econometrics, machine learning (RF, XGBoost, feature engineering), and regime-based modelling.

     

  • Identify and manage modelling risks including lookahead bias, data leakage, overfitting, slippage, and market-impact effects.

     

  • Design, test, and oversee multi-system, multi-regime strategies for real portfolio implementation.

     

  • Work directly with the CIO on strategy refinement, validation, and portfolio construction.

     

  • Produce and communicate regular strategy updates across digital channels (email, dashboards, WhatsApp Business, etc.).

     

  • Manage digital distribution lists, product access links, and ensure smooth communication with internal/external stakeholders.

     

  • Partner with Sales, Marketing, and Compliance to ensure materials meet brand, regulatory, and client standards.

     

Qualifications & Experience

  • Strong academic background in mathematics, statistics, quantitative finance, engineering, computer science, or related fields.

     

  • Demonstrated ability to take ownership of live portfolios and deploy systematic strategies quickly-ideally with experience stepping into portfolio responsibility on tight timelines.

     

  • Minimum 2+ years of experience in quantitative research or systematic portfolio management within asset management, hedge funds, or proprietary trading.

     

Technical Skills

  • Advanced Python engineering skills with experience building modular, maintainable research and production systems (NumPy, pandas, scikit-learn, XGBoost, statsmodels, plotting libraries, MLOps utilities).

     

  • Strong knowledge of backtesting frameworks, walk-forward and rolling-window testing, and model-validation best practices.

     

  • Practical experience managing model bias, operational risk, and research-to-production transitions.

     

  • Equities experience preferred; strong candidates from macro, FX, fixed income, or commodities backgrounds will also be considered.

     

Job Details

Goodman Masson logo
Recruitment Agencies

17 days ago

clicks

Systematic Portfolio Manager

at Goodman Masson

ExperiencedNo visa sponsorship

Not specified

Currency not set

City: Muscat

Country: Oman

Systematic Portfolio Manager to relocate to Muscat, Oman to run and systematize multiple live sub-portfolios within three months, developing, testing and deploying quant-driven investment systems. You will build production-quality Python codebases, apply econometrics and machine learning (including RF and XGBoost), manage model risk and oversee multi-system, multi-regime strategies while working closely with the CIO. The role also includes production deployment, stakeholder communication, digital distribution management and partnering with Sales, Marketing and Compliance.

Full Job Description

Systematic Portfolio Manager – Relocation to Oman

Location: Muscat, Oman

Employer: Growing Investment Management Firm

We’re seeking a talented Systematic Portfolio Manager, who is open to relocating to Oman to join a rapidly expanding investment management firm. This is a high-impact role for someone who wants real ownership, fast responsibility, and the opportunity to build and run systematic portfolios in a dynamic, entrepreneurial environment.

Role Overview

As a Systematic Portfolio Manager, you will take immediate responsibility for several live sub-portfolios, transitioning them to fully systematic oversight within the first three months. You will lead research, development, deployment, and ongoing management of data-driven investment systems, working closely with the CIO and broader investment team.

Key Responsibilities

  • Take over and systematize multiple existing sub-portfolios within 3 months, including signal integration, risk controls, and performance analytics.

     

  • Lead full-cycle development of quantimental investment systems-from hypothesis and empirical testing to production deployment.

     

  • Build modular, production-quality Python codebases using modern analytics, ML, and statistical tools.

     

  • Conduct research across econometrics, machine learning (RF, XGBoost, feature engineering), and regime-based modelling.

     

  • Identify and manage modelling risks including lookahead bias, data leakage, overfitting, slippage, and market-impact effects.

     

  • Design, test, and oversee multi-system, multi-regime strategies for real portfolio implementation.

     

  • Work directly with the CIO on strategy refinement, validation, and portfolio construction.

     

  • Produce and communicate regular strategy updates across digital channels (email, dashboards, WhatsApp Business, etc.).

     

  • Manage digital distribution lists, product access links, and ensure smooth communication with internal/external stakeholders.

     

  • Partner with Sales, Marketing, and Compliance to ensure materials meet brand, regulatory, and client standards.

     

Qualifications & Experience

  • Strong academic background in mathematics, statistics, quantitative finance, engineering, computer science, or related fields.

     

  • Demonstrated ability to take ownership of live portfolios and deploy systematic strategies quickly-ideally with experience stepping into portfolio responsibility on tight timelines.

     

  • Minimum 2+ years of experience in quantitative research or systematic portfolio management within asset management, hedge funds, or proprietary trading.

     

Technical Skills

  • Advanced Python engineering skills with experience building modular, maintainable research and production systems (NumPy, pandas, scikit-learn, XGBoost, statsmodels, plotting libraries, MLOps utilities).

     

  • Strong knowledge of backtesting frameworks, walk-forward and rolling-window testing, and model-validation best practices.

     

  • Practical experience managing model bias, operational risk, and research-to-production transitions.

     

  • Equities experience preferred; strong candidates from macro, FX, fixed income, or commodities backgrounds will also be considered.