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 predictive 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 practises and creating high impact, high value training models.
Communicate results and recommendations to stakeholders, including non-technical audiences, using data visualization techniques.

Required Skills:

3+ 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 (eg, 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.
Bachelors or Masters degree (or equivalent) in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Operations Research, or a related field

Data Science Engineer

Job Description