Data Scientist (Machine Learning & Financial Analytics)
Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Oct 13, 2026.
This role requires the candidate to work on-site in Tokyo, Japan.
Client Overview
Our client is a global technology consulting company specializing in Artificial Intelligence (AI), Data Science, Machine Learning, and Digital Transformation (DX). The organization partners with leading financial institutions and enterprise clients to develop advanced analytics solutions that improve business performance, optimize operations, and accelerate digital innovation.
As demand for AI-driven financial analytics continues to grow, the company is expanding its Data Science team to develop machine learning models, predictive analytics, and production-ready AI solutions that address complex business challenges across the financial services industry.
Job Role
The Data Scientist will develop and deploy machine learning solutions that help financial institutions transform data into actionable business insights. Working alongside senior Data Scientists, AI Consultants, and cross-functional project teams, this role supports end-to-end analytics projects ranging from data preparation and feature engineering to predictive model development and MLOps implementation.
This position is ideal for professionals who enjoy solving complex business problems through data-driven decision-making while continuously advancing their expertise in machine learning and financial analytics.
Key Responsibilities
Develop, train, and evaluate machine learning models using structured (tabular) data for financial industry use cases.
Perform data preprocessing, feature engineering, exploratory data analysis, and model validation using Python.
Support the deployment and operationalization of machine learning models with MLOps best practices.
Collaborate with senior Data Scientists on AI and analytics projects for enterprise financial clients.
Work closely with AI Consultants to understand business requirements and translate them into analytical solutions.
Design reusable machine learning frameworks, analytical methodologies, and model libraries to improve project efficiency.
Monitor model performance and continuously optimize predictive accuracy and operational effectiveness.
Contribute to technical documentation, knowledge sharing, and continuous improvement initiatives across the Data Science team.
Candidate Requirements
Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, Information Science, Econometrics, Engineering, or a related quantitative discipline.
Minimum 1 year of practical experience in Machine Learning or Data Science.
Hands-on experience analyzing structured (tabular) datasets using machine learning techniques.
Strong programming skills in Python (experience with R is an advantage).
Experience developing predictive models from data preparation through evaluation and deployment.
Familiarity with data platforms such as Snowflake, Databricks, BigQuery, or similar technologies is preferred.
Strong analytical thinking and problem-solving skills with the ability to translate business challenges into data-driven solutions.
Business-level Japanese proficiency (approximately JLPT N1) is mandatory.
Professional English reading and communication skills are preferred.
Foreign candidates should hold (or be eligible for) an appropriate Japanese working visa, including Permanent Resident, Highly Skilled Professional, or Engineer/Specialist in Humanities/International Services.