Apply supervised and unsupervised machine learning techniques, such as linear and logistic regression, decision trees, and k-means clustering, ensemble models, Neural Networks
Develop analyses segmentation, propensity models, KPI deep dives, marketing efficiency, behavioural clustering, customer lifetime value and customer journey analytics.
Curate audiences and inform engagement tactics to enable differentiated, relevant marketing touches across CRM channels (email, in-app, push).
Synthesize analytics and statistical approaches into easy-to-consume storylines, both visually and verbally, and provide indicated actions for executive audiences.
Capture business requirements for data and analytic solutions and collaborate with the Marketing team to ensure business requirements align with business needs.
Analyze content promotions and surface insights that will help drive viewership and a more loyal customer base.
Support day-to-day collaboration with Marketing to communicate insights and recommend data-informed strategies
Experience in Python
Experience in working with large datasets with statistical analysis
Capability to identify and troubleshoot potential Business issues
Experience in Data Science/Machine Learning
Familiarity with a broad set of modelling techniques; aptitude in mathematics, probability, algorithms, experimentation methods, hypothesis testing
Hands-on programming/implementation ability in R/Python/Java, NO-SQL DB s
Knowledge of Big Data Tools: Real-Time streaming engines, Messaging Queues, Hadoop, PySpark ( added advantage)
Prior experience working any cloud infrastructures such as AWS, GCP, Azure
Ability to write production-level code and experience pushing machine learning models to production
3+ years of experience building data science models (Regression, Decision Trees, K-Means, ensemble models, Neural Networks, etc.).
3+ years of hands-on experience with commercial applications of machine learning
Hands-on experience with Text mining and Computer vision techniques
Experience with large data sets and analytical tools.
Proficiency in scripting languages (SQL, Python, R, etc.).
Knowledge of a dashboarding language (Tableau, Looker, etc.) or equivalent report building experience not required but a plus Other desired qualifications: - Strong curiosity, leadership and business acumen.
Passionate about using data to drive strategy and product recommendations.
Experience in Media company, subscription-based businesses or eCommerce preferred.
In-depth knowledge of statistics and machine learning algorithm
Curious and careful about the business impact of their work
Able to work collaboratively and proactively alongside scientists, engineers, and analysts
Experience in deep learning, causal inference, uplift modelling, or econometrics is a bonus
Good Python programming skills, intimate with the Python data science stack
Knowledge of best practices for software development and data organization, and pleasure in working in an open-source environment (Github is at the core of our workflow)
Participate in data architecture decisions and partner with technology teams to implement models/algorithms in the production
Manage the continuous improvement of data science and analytics by researching industry best practices and staying up-to-date on analytical practices
Integrate data science solutions into current business processes
Experience with Microservices and model production with Containers (like Docker) will be advantageous