Data Scientist

About Cybage:

Cybage Software is a technology consulting organization specializing in outsourced product engineering services. Our unique offerings span the technological spectrumfrom cutting-edge software development to transformative digital strategies. In 1995, Cybage was founded with a mission to revolutionize the product engineering landscape, empowering businesses to soar above their limitations. What commenced as a modest venture has transformed into a pioneering force, shaping the digital future with innovative solutions tailored to our clients' unique needs.

Job Description

Key Responsibilities:

• Analyze historical video survey data (Purchase Intent, Brand Favourability, Facial Coding metrics, etc.) to identify performance drivers.
• Develop predictive models that can forecast ad performance metrics based on creative features, audience segments, and historical trends.
• Apply statistical, machine learning, and deep learning techniques to extract insights and build scalable prediction pipelines.
• Collaborate with business stakeholders to translate requirements into technical solutions.
• Design validation frameworks to benchmark predictive performance against actual survey outcomes.
• Build dashboards/visualizations for business teams to interpret predictive outcomes.
• Continuously refine and improve model accuracy by incorporating new data sources and feedback loops.

Required Skills & Experience:

• Bachelors/Masters degree in Data Science, Computer Science, Statistics, Applied Mathematics, or related fields.
• 10+ years of experience in machine learning / predictive analytics / data science.
• Strong proficiency in Python/R and ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost).
• Hands-on experience with predictive modeling, regression, classification, and time-series forecasting.
• Experience in feature engineering from unstructured data (e.g., video metadata, textual content, tags).
• Familiarity with media/advertising analytics (ad effectiveness, consumer insights, brand lift studies) is a strong plus.
• Strong SQL knowledge and experience with large datasets (10k+ records, multiple metrics).
• Experience with computer vision (video/image analysis) for extracting features from creatives.
• Excellent communication skills to explain technical results to non-technical stakeholders.

Nice to Have:

• Knowledge of cloud platforms (AWS) for model deployment and scaling.
• Exposure to natural language processing (NLP) for analyzing ad scripts, captions, or metadata.
• Experience with facial coding / emotion AI frameworks.
• Previous experience in adtech, martech, or consumer research domains.