Sr. Finance Analyst - Data Science/ Analytic

AMD; Penang; Hybrid; MYR 90,000 - 120,000; Full time

Job summary

A leading semiconductor company is seeking a Senior Finance Analyst with expertise in data science and analytics. In this hybrid role, you will transform financial data into actionable insights, develop predictive models, and automate processes to enhance efficiency. The ideal candidate should have over 3 years of experience in data science, strong proficiency in SQL and Python, and excellent problem-solving skills to effectively manage large datasets and collaborate with cross-functional teams. This position is based in Penang, Malaysia.

Qualifications

• 3+ years of experience in data science, financial analytics, or business intelligence.
• Solid understanding of statistics and machine learning algorithms.
• Strong business acumen with the ability to communicate technical concepts.

Responsibilities

• Develop and deploy predictive models using machine learning algorithms.
• Design and implement generative AI solutions for workflow automation.
• Build and maintain data pipelines and infrastructure.
• Automate reporting processes for accuracy and efficiency.
• Manage master data across financial systems.

Skills

SQL

Python

Machine Learning

Data Visualization

Problem Solving

Education

Bachelor’s degree in Finance, Data Science, Accounting, Statistics, or a related field

Tools

Power BI

Tableau

Scikit-learn

TensorFlow

PyTorch

Airflow

Snowflake

Hadoop

Spark

Job description

Sr. Finance Analyst - Data Science/ Analytic

This hybrid role leverages advanced data science and AI expertise to transform financial and business data into actionable insights, drive predictive modeling, and automate processes for improved efficiency and strategic decision-making. The analyst will collaborate across finance, sales, operations, and data engineering teams to deliver scalable solutions that optimize performance, minimize manual tasks, and support business growth.

THE PERSON

You are a passionate data science professional with strong SQL and programming skills (Python preferred), and a solid understanding of statistics and machine learning algorithms. Detail-oriented and business-savvy, you thrive in fast-paced environments, effectively managing competing priorities and meeting deadlines. You excel in collaborative settings, bringing project management and stakeholder engagement skills, and are comfortable working with large datasets and complex financial systems.

Your strong problem-solving abilities are complemented by an understanding of master data and its impact on financial accuracy. With keen business acumen, you can translate data insights into strategic financial outcomes and communicate effectively with both technical and non-technical stakeholders.

KEY RESPONSIBILITIES

• Develop and deploy predictive models (e.g., credit risk, fraud detection, revenue forecasting) using machine learning algorithms and time-series techniques (ARIMA, Prophet, XGBoost, Random Forest).
• Design and implement generative AI solutions (LLMs, GANs) for workflow automation, information retrieval, and decision support.
• Build and maintain scalable data pipelines and infrastructure using tools like Airflow, KNIME, Snowflake, Hadoop, and Spark.
• Automate reporting processes and improve data pipelines for accuracy and efficiency.
• Perform exploratory data analysis and create visualizations (Power BI, Tableau, Plotly, Matplotlib) to communicate insights to stakeholders.
• Manage master data across financial systems to ensure consistency and integrity.
• Collaborate with cross-functional teams to translate business needs into technical requirements and deliver impactful solutions.
• Ensure compliance with data governance, financial regulations, and quality standards.
• Continuously experiment with new AI tools and techniques to drive innovation and process improvement.

PREFERRED EXPERIENCE

• 3+ years of experience in data science, financial analytics, or business intelligence.
• Proficiency in Python, SQL, and ML libraries (Scikit-learn, TensorFlow, PyTorch).
• Experience with data visualization tools and big data technologies.
• Strong business acumen and ability to communicate technical concepts to non-technical stakeholders.
• Exposure to ERP systems (SAP S4 preferred), master data management, and financial reporting.
• Experience with process improvement, automation, and project-based work.
• Excellent stakeholder management and communication skills.

ACADEMIC CREDENTIALS

• Bachelor’s degree in Finance, Data Science, Accounting, Statistics, or a related field.
• Chartered Financial Analyst (CFA), Master of Business Administration (MBA), or Certified Public Accountant (CPA) is an advantage.