Data Scientist– PH.D Statistics, Machine Learning or Deep Learning

TeamPlus; Bengaluru, Chennai; Presencial; INR 2 500 000 - 4 000 000; Tempo integral

Resumo da oferta

TeamPlus Staffing Solution Pvt Ltd seeks a Senior Analyst in Data Science with a PhD in Statistics, ML or DL. The role focuses on designing, developing and deploying advanced ML models for fraud detection across large transactional datasets.

Deep knowledge of Graph Neural Networks, Transformers, Variational Auto Encoders and NLP is preferred. You will build data pipelines using SQL, Python and AWS services, and collaborate with compliance and risk teams.

Qualificações

• PhD required in Statistics, ML or DL.
• Completion of PhD is a strict requirement.
• 1-15 years of experience; 1+ years in Data Science preferred.
• Experience in FinTech, Payments or Banking is beneficial.

Responsabilidades

• Design, develop, and deploy ML models for fraud detection.
• Work with GNNs, Transformers, VAEs and other DL models.
• Perform data analysis, feature engineering and statistical modeling on large datasets.
• Collaborate with compliance, risk, and operations to translate requirements into data science solutions.
• Build data pipelines using SQL, Python and AWS services (SageMaker, Redshift, S3, Lambda).
• Monitor model performance, prepare reports, and ensure alignment with regulatory standards.

Conhecimentos

Python

SQL

Machine learning concepts

Graph Neural Networks

Transformers

Variational Autoencoders

NLP

Formação académica

PhD in Statistics, ML or DL

Ferramentas

SageMaker

Redshift

S3

Lambda

Feedzai

Descrição da oferta de emprego

Senior Analyst – Data Science-PH.D in Statistics, Machine Learning or Deep Learning

Qualification:

PhD in Statistics, Machine Learning or Deep Learning

Years of Experience

1-15 years (Completion of PhD is a strict requirement)

Permanent / Contract (If contract, period ?)

Taramani, Chennai – 600113, Tamil Nadu, India/

Bellandur Village, Bengaluru, Karnataka

Role

Design, develop, and deploy advanced machine learning models for fraud detection.

Have in-depth knowledge in Graph Neural Networks (GNN), Transformers,

Variational Auto Encoders, Deep Learning Models and advanced ML concepts.

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 and ensure solutions align with regulatory standards and organizational policies. .

Experience:

1+ years of experience in Data Science and experience in FinTech, Payments, Banking is preferred.

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.

• Implementing existing research / developing novel algorithms, technical solutions to combat fraud and anti-money laundering (AML) use cases.

Exposure to Feedzai or similar fraud detection platforms and AWS experience is preferred.

Strong communication and collaboration skills, with the ability to work across cross-functional teams.