Data Scientist

Affinity Global; Mumbai; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Affinity is a global AdTech company developing solutions that help publishers monetize more effectively and enable advertisers to reach the right audiences. We are seeking an experienced Data Scientist to contribute to AI/ML algorithms for ad decisioning, bid auctioning, and optimization.

You will manage data, develop modelling techniques, and communicate insights to stakeholders. The role requires strong collaboration with product, engineering, and sales teams to ensure seamless integration of

Qualifications

• 5+ years of proven experience as a Data Scientist in Digital Advertising.
• Extensive knowledge of ML, neural networks, and statistics for data modelling and mining.
• Experience with ML libraries (TensorFlow, PyTorch, scikit-learn, XGBoost) and real-time data processing.
• Proficiency in Python, R, SQL, or Apache Spark.
• Bachelor's or Master's degree in CS, AI, ML, Statistics, OR related field.

Responsibilities

• Design and develop AI/ML algorithms for ad decisioning, bid auctioning, ad creative optimization, forecasting, and data classification in Digital Advertising.
• Identify valuable data sources and automate data engineering and ETL processes from ad serving events.
• Develop strategies for data preparation, including structured and unstructured data.
• Perform feature engineering and analyse large amounts of data from ad serving event logs to identify trends, patterns, and anomalies in bidding and ad decisioning.
• Ensure data privacy and security while conducting data analysis and modelling.
• Conduct experiments to validate hypotheses and test new algorithms.
• Build MVPs using a proof‑of‑concept approach, focusing on scalability, speed, and accuracy.
• Build and maintain models, dashboards, and automated reports to monitor performance and support decision‑making.
• Collaborate with cross‑functional teams, such as product, engineering, and sales, to ensure seamless integration of algorithms with other systems and processes.
• Stay up to date with the latest industry developments, advancements, and technologies in prediction and classification.
• Understand and implement diverse strategic ML/AI algos as per industry best practices and create high impact training models.
• Communicate results and recommendations to stakeholders, including non‑technical audiences, using data visualization techniques.

Skills

Data Science

Advertising Analytics

ML/AI Modeling

Python

SQL

TensorFlow/PyTorch

Data Visualization

Education

Bachelor's/Master's in CS/AI/Stats

Tools

TensorFlow

PyTorch

scikit-learn

XGBoost

Apache Spark

Job description

Affinity is pioneering new frontiers in AdTech: developing solutions that push past today’s limits and open up new opportunities. We are a global AdTech company helping publishers discover better ways to monetize and enabling advertisers to reach the right audiences through new touchpoints. Operating across 10+ markets in Asia, the US, and Europe with a team of over 650 experts, we are building privacy-first ad infrastructure that opens up opportunities beyond the walled gardens.

Role: Data Scientist

About Role:

We are seeking an experienced Data Science Engineer to join our team and work on AI/ML algorithms for various ad decisioning, bid auctioning, ad creative optimization, forecasting, and data classification needs in the field of Digital Advertising. In this role, you will be responsible for managing data, developing and implementing modelling techniques, and communicating insights to stakeholders.

• Design and develop AI/ML algorithms for ad decisioning, bid auctioning, ad creative optimization, forecasting, and data classification in Digital Advertising.
• Identify valuable data sources and automate data engineering and ETL processes from ad serving events.
• Develop strategies for data preparation, including structured and unstructured data.
• Perform feature engineering and analyse large amounts of data from ad serving event logs to identify trends, patterns, and anomalies in bidding and ad decisioning.
• Ensure data privacy and security while conducting data analysis and modelling.
• Conduct experiments to validate hypotheses and test new algorithms.
• Build Minimum Viable Products (MVPs) using a proof‑of‑concept approach, focusing on scalability, speed, and accuracy.
• Build and maintain models, dashboards, and automated reports to monitor performance and support decision‑making.
• Collaborate with cross‑functional teams, such as product, engineering, and sales, to ensure seamless integration of algorithms with other systems and processes.
• Stay up to date with the latest industry developments, advancements, and technologies in prediction and classification.
• Understanding and implementing diverse strategic ML/AI algos as per industry best practices and creating high impact, high value training models.
• Communicate results and recommendations to stakeholders, including non‑technical audiences, using data visualization techniques.

Required Skills:

• 5+ years of proven experience as a Data Scientist.
• Experience applying Data Science techniques in the field of Digital Advertising is a must.
• Extensive knowledge and practical experience in machine learning, neural networks, and statistics, with a focus on data modelling, engineering and mining.
• Understanding of machine learning and operations research, along with experience using machine learning libraries (e.g., TensorFlow, PyTorch, scikit‑learn, XGBoost, etc.) and real‑time data processing.
• Understanding latest advancements announced via industry research communities and research papers.
• Proficiency in programming languages like R, Julia, Python, SQL, or Apache Spark.
• Excellent analytical and problem‑solving aptitude, critical thinking skills, strong mathematical abilities (statistics, algebra), and effective communication and presentation skills.
• Experience using Business Intelligence Tools and Distributed cloud data frameworks.
• Curiosity and a strong desire for continuous learning.
• Bachelor's or Master's degree (or equivalent) in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Operations Research, or a related field.