Senior Data Scientists

2 weeks ago

Manila, National Capital Region, Philippines Agileit IT consultancy Full time

Position: Senior Data Scientist

Location: Remote

Employment Type: Contract, Full-time

About the Role

We are seeking a highly skilled Senior Data Scientist with strong experience in the financial sector to lead advanced analytics, machine learning, and quantitative modelling initiatives. This role will work closely with investment, finance, and risk teams to unlock insights, improve forecasting accuracy, and drive data-driven strategies across the organization. You will act as a technical expert, mentor junior team members, and shape best practices in modelling and data science delivery.

Key Responsibilities

Machine Learning & Advanced Modelling

  • Lead design and development of predictive and statistical models for forecasting, asset performance, risk scoring, credit assessment, fraud detection, and scenario analytics.
  • Build and optimize models using time-series forecasting, regression, classification, and advanced ML techniques.
  • Oversee model validation, documentation, monitoring, and continuous performance improvement.

Financial Analytics & Business Impact

  • Translate complex financial problems into actionable analytical solutions.
  • Partner with finance, risk, investment, and strategy teams to support forecasting, capital planning, valuation analysis, and business performance insights.
  • Communicate results and recommendations to senior management through clear data storytelling.

Data Pipelines & Model Deployment

  • Collaborate with data engineering to build scalable pipelines and integrate models into production systems.
  • Ensure high-quality, well-governed datasets for modelling and analytics.
  • Support development of enterprise data platforms, data lakes, and MLOps frameworks.

Requirements

Education & Experience

  • Bachelor's or Master's in Data Science, Computer Science, Statistics, Applied Mathematics, Finance, or related field.
  • 5–8+ years of data science experience, with significant exposure to the financial industry (banking, fintech, asset management, or insurance).

Technical Skills

  • Strong proficiency in Python, SQL, and ML libraries (scikit-learn, XGBoost, statsmodels; deep learning a plus).
  • Experience with cloud platforms (AWS, Azure, or GCP) and MLOps workflows.
  • Solid understanding of financial datasets, time-series modelling, quantitative analysis, and risk models.

Soft Skills

  • Strong communication skills with the ability to convey complex insights to non-technical stakeholders.
  • Excellent problem-solving and critical-thinking abilities.
  • Ability to lead projects end-to-end and operate independently.

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