Senior Analyst - Data Science

LatentView Analytics Ltd.; Chennai District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Darwinbox Digital Solutions Pvt. Ltd. is seeking a Senior Analyst - Data Science to design and deploy fraud-prediction models using machine learning across fintech datasets.

The role emphasizes end-to-end model development, feature engineering, and collaboration with compliance and risk teams to ensure regulatory alignment. The ideal candidate has 3–8 years of experience, strong skills in Python, SQL, AWS (SageMaker), and a track record of delivering production ML solutions with cross-functional

Qualifications

• 3–8 years of data science experience, fintech preferred.
• BS/MS in data science, CS, statistics, or applied mathematics.
• Proficiency in Python, SQL, and statistical techniques.
• Experience with ML methods and AWS cloud services.

Responsibilities

• Assist in designing, developing, and deploying ML models for fraud prevention.
• Perform data analysis, feature engineering, and statistical modeling on large-scale datasets.
• Collaborate with compliance, risk, and operations to translate requirements into data solutions.
• Build and maintain data pipelines using SQL, Python, and AWS services (SageMaker, Redshift, S3, Lambda).
• Support integration of ML models into production environments, including Feedzai.
• Monitor and evaluate model performance, prepare reports, and propose improvements.
• Ensure solutions align with regulatory standards and policies.
• Provide guidance and mentorship to junior analysts.

Skills

Python

SQL

Statistics

Machine learning

NLP

Data analysis

Communication

Education

Bachelor's or Master's in data science, CS, statistics, or applied mathematics

Tools

SageMaker

Redshift

S3

Lambda

Feedzai

Job description

Designation: Senior Analyst - Data Science

Level: L2

Experience: 3 to 8 Years

Job Description:

We are seeking an Senior Analyst - Data Science to develop fraud prediction models using machine learning. The role involves contributing to the development and deployment of machine learning models and data-driven solutions to detect suspicious activity, mitigate financial crime, and ensure compliance. The ideal candidate will combine strong technical expertise with a solid understanding of machine learning and experience in development of end-to-end model development lifecycle.

Responsibilities:

• Assist in designing, developing, and deploying machine learning models for fraud prevention.
• Perform data analysis, feature engineering, and statistical modeling on large-scale transactional datasets.
• Collaborate with compliance, risk, and operations teams to translate requirements into actionable data science solutions.
• Build and maintain data pipelines using SQL, Python, and AWS services (SageMaker, Redshift, S3, Lambda).
• Support the integration of ML models into production environments, including Feedzai.
• Monitor and evaluate model performance, prepare reports, and recommend improvements.
• Ensure solutions align with regulatory standards and organizational policies.
• Provide guidance and mentorship to junior analysts where required.

Required Skillsets:

• Education: Bachelor's/master's degree in data science, Computer Science, Statistics, Applied Mathematics, or a related field.
• Experience: 3-8 years of experience in Data Science, with at least 2+ years in FinTech, Payments, Banking.
• Strong programming and analytical skills with Python, SQL, and statistical techniques.
• Experience in applying machine learning methods such as classification, clustering, anomaly detection, and NLP.
• Hands-on experience in AWS cloud services (SageMaker, S3).
• Exposure to Feedzai or similar fraud detection platforms preferred.
• Strong communication and collaboration skills, with the ability to work across cross-functional teams.