Develop and implement AI/ML models to solve complex problems in the media space (e.g., content tagging, recommendation engines, audience segmentation).
Use NLP techniques to process, analyze, and derive insights from unstructured text, subtitles, social media content, etc.
Analyze large datasets from media platforms to extract meaningful patterns and trends.
Work closely with data engineers and business stakeholders to translate business problems into analytical solutions.
Build, test, and deploy predictive models and algorithms using Python.
Perform model evaluation, validation, and tuning to improve performance.
Present insights and results through compelling visualizations and storytelling.
Key Skills:
Programming: Proficiency in Python and relevant libraries (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
Machine Learning: Strong understanding of supervised and unsupervised ML techniques.
NLP: Experience with NLP libraries like SpaCy, NLTK, HuggingFace, Transformers, etc.
AI: Understanding of deep learning models and their applications in text/audio/image data.
Data Handling: Experience working with large, unstructured datasets.
Media Domain Knowledge (Preferred): Exposure to content analysis, ad targeting, viewer analytics, or similar.
Good to Have:
Familiarity with cloud platforms (AWS, GCP, Azure).
Knowledge of Big Data tools (Spark, Hadoop) is a plus.
Experience with SQL and data visualization tools (Tableau, Power BI).
Qualifications:
Bachelors or Masters degree in Computer Science, Data Science, Statistics, or a related field.
Relevant certifications in AI/ML or Data Science are a plus.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Analytics - OtherRole: Data Science & Analytics - OtherEmployement Type: Full time