Data Scientist

Description

Matrix is seeking a mid-level Data Scientist (5–7 years’ experience) to build, validate, and operationalize analytics and machine learning solutions for fraud, AML, and financial crime use cases. In this client-facing role, you will work with complex transactional datasets to develop detection strategies, support implementations, and communicate insights to both technical and non-technical stakeholders.

Key Skills

Strong proficiency in Python (NumPy, Pandas, SciPy, scikit-learn), solid machine learning foundations, experience with distributed processing (e.g., PySpark), and the communication skills to explain analytical results and recommendations clearly.

What You’ll Do

• Data analysis & modeling: Explore client data, perform data cleaning and preprocessing, engineer features, and develop/tune machine learning models for fraud and financial crime detection.
• Client & cross-functional collaboration: Partner with client stakeholders and internal teams (e.g., Product, Engineering, Research, Delivery) to understand objectives, translate needs into analytical approaches, and support successful adoption.
• Technical delivery: Contribute to project execution by producing reproducible analyses, supporting data validations, and helping build scalable pipelines/prototypes used in implementations and ongoing monitoring.
• Product & solution improvement: Identify repeatable patterns and gaps, contribute to reusable assets (features, checks, playbooks), and share recommendations that improve platform capabilities and delivery efficiency.
• Communication: Present findings, model performance, and recommended detection strategies to technical and business audiences through clear narratives and practical next steps.

What We’re Looking For

• Domain experience: Experience in fraud and/or AML, financial crime, transaction monitoring, payments risk, or related risk analytics.
• Programming: Strong Python skills, including the scientific stack (NumPy, Pandas, SciPy, scikit-learn); experience with distributed processing (e.g., PySpark) is a plus.
• Machine learning: Practical experience with supervised/unsupervised learning, model evaluation, and translating model outputs into risk strategy or operational improvements.
• Data workflows: Experience with data cleaning, feature engineering, and building repeatable analytical workflows; exposure to orchestration/query tools (e.g., Airflow, Trino) is a plus.
• Communication: Strong verbal and written communication skills; able to explain complex analytical work to varied stakeholders.
• Problem solving: Strong analytical thinking and attention to detail to diagnose data issues and solve complex financial crime challenges.

Education

Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Data Science, Statistics, Applied Mathematics, or a related discipline.

Why Matrix

Matrix is a global, dynamic, fast-growing technical consultancy leading technology services company with 13000 employees worldwide. Since its foundation in 2001, Matrix has made more travelers and acquisitions and has executed some of the largest, most significant. The company specializes in implementing and developing leading technologies, software solutions, and products. It provides its customers with infrastructure and consulting services, IT outsourcing, offshore, training and assimilation, and Ves as representatives for the world's leading software vendors. With vast experience in private and public sectors, ranging from Finance, Telecom, Health, Hi-Tech, Education, Defense, and Secu city, Matrix's customer base includes guest organizations in Israel and a steadily growing client base worldwide.

We are comprised of talented, creative, and dedicated individuals passionate about delivering innovative solutions to the market. We source and foster the best talent and recognize that all employee's contributions are integral to our company's future.

Matrix- success is based on a challenging work environment, competitive compensation and benefits, and rewarding career opportunities. We encourage a diverse work environment of sharing, learning, and ceding together. Come and join the winning team! You'll be challenged and have fun in a highly respected organization. To Learn More, Visit Matrix -ifs. Com,