Senior Data Scientist - Financial Services

Manila, Philippines; Singapore; On-site; USD 80,000 - 130,000; Full time

Job summary

An established industry player is on the lookout for a Senior Data Scientist with a wealth of experience in financial services. This pivotal role involves leveraging data insights to develop predictive models that drive strategic decisions in banking and payments. You will lead the deployment of advanced machine learning techniques and collaborate with cross-functional teams to communicate findings effectively. If you thrive in a fast-paced environment and are passionate about transforming complex data into actionable insights, this opportunity is perfect for you. Join a dynamic team and make a significant impact in the financial sector!

Qualifications

• 7+ years of experience in data science and analytics focusing on banking and payments.
• Proficiency in statistical modeling and machine learning techniques.

Responsibilities

• Lead the development of machine learning models for banking and payments.
• Analyze large datasets using SAS, Hadoop, R, SQL, and Python.

Skills

Statistical Modeling

Machine Learning

Data Analysis

Python

SQL

Data Visualization

Problem-Solving

Tools

SAS

Hadoop

R

Hive

Excel

PowerPoint

Job description

Role

Senior Data Scientist - Financial Services

Job Overview

We are seeking a highly experienced and motivated Senior Data Scientist to join our team, focusing on the banking, payments, or related industries. The ideal candidate will have over 7 years of hands-on analytics experience and deep proficiency in statistical modeling, machine learning techniques, and programming tools. This individual will collaborate with business and technical teams to leverage data insights and develop advanced predictive models that inform strategic decision-making.

Key Responsibilities

1. Lead the development and deployment of machine learning models and statistical analyses to solve complex business problems within banking and payments industries.
2. Analyze large and complex datasets using tools such as SAS, Hadoop, R, SQL, Python, and Hive, ensuring data integrity and optimizing analytical processes.
3. Apply various statistical techniques including Neural Networks, Gradient Boosting, Linear & Logistic Regression, Decision Trees, Random Forests, Markov Chains, Support Vector Machines, Clustering, Principal Component Analysis, and Factor Analysis to derive actionable insights.
4. Develop and validate predictive models, conduct experiments, and generate insights to guide business strategies and operational improvements.
5. Communicate findings effectively through data visualizations and presentations using Excel and PowerPoint, collaborating with cross-functional teams.
6. Lead data storytelling and presentation efforts, ensuring clear communication of technical findings to both technical and non-technical stakeholders.

Required Qualifications

1. 7+ years of experience in data science, analytics, or related fields, with a focus on banking, payments, or similar industries.
2. Proficiency with data analysis and programming tools such as SAS, Hadoop, R, SQL, Python, and Hive.
3. Deep expertise in statistical modeling and machine learning techniques as listed above.
4. Strong skills in creating compelling data visualizations and presentations using Excel and PowerPoint.
5. Excellent problem-solving and analytical skills, with the ability to translate complex data into actionable insights.
6. Ability to manage multiple projects in a fast-paced environment.