Lead Data Scientist

Role Summary and Impact

The Data Scientist (Senior Manager/Lead, Data Science ) reports to the Director, Data Science working to design, develop & deploy data and analytics solutions for a leading client across markets, the portfolio of brands. You should have a strong understanding of the concepts and tools in data enrichment, media analytics and measurement, experimentation and research space. You will become familiar with internal modelling and technology products to partner with data strategy and deployment teams for implementing at scale. 

The Senior Manager/Lead, Data Scientist following the direction of the Director, Data Science and is responsible for the design and the delivery commitments for the client for data and analytics solutions, including data and technical requirements, data management and manipulation, insights and analytics, dashboards and visualisation.

What You Will Do

• Actively explore and identify the latest techniques related to AI, ML and data exploration analysis.
• Perform exploratory data analysis, hypothesis testing, data preparation and product prototyping based on modern statistical and ML/AI methods.
• Research, develop and applying ML/AI models to solve business and clients problems effectively.
• Use your knowledge to anticipate, identify, and address data issues related to redundancies, quality, and bias. Apply rigorous data cleaning and preprocessing techniques to ensure high-quality data for modelling.
• Lead data science projects, blending various data science techniques as needed to achieve optimal performance and actionable insights. Continuously explore innovative and novel approaches to improve modelling accuracy and efficiency.
• Assist with the application of Choreograph and third-party solutions for data assimilation, enrichment and analytics for delivering data sets and insights for strategic planning, activation and measurement.
• Work with cross-functional teams to build and execute industry-leading data and audience analytics solutions.
• Apply your communication, collaboration and emotional intelligence skills to effectively convey complex technical concepts to both technical and non-technical stakeholders. Facilitate cross-functional collaboration with other teams and departments.

Skills And Experience 

• Bachelors or advanced degree in Statistics, Economics, Business, Math, or Sciences is preferred.
• Work experience of 7+ years of experience in applied data science, analytics, or ML engineering.
• Strong math or statistics background, specifically strong grasp of descriptive and probabilistic theories, sampling.
• Strong analytic and problem-solving skills, understanding and experience in application of AI methodologies for data manipulation and insight.
• Experience in building and execution of advanced solutions for audience analytics and insights.
• Strong SQL skills and comfort working with large-scale, multi-source data.
• Experience with version control (Git) and collaborative coding workflows.
• Advanced Python skills, incl. pandas, numpy, scikit-learn, scipy, statsmodels for modelling and analytics.
• Solid understanding of predictive modelling, feature selection, and model evaluation (AUC, lift, calibration, etc.).
• Experience with gradient boosting methods (xgboost, lightgbm, or catboost).
• Experience with Power BI or other data visualization tools especially geo coded data is a big plus.
• Sufficient knowledge of data governance practices including data QA, general naming taxonomy, data & platform integration, etc.
• Ability to foster collaborative relationships with cross-functional team.
• Excellent written, oral, and presentation communication.
• Ability to communicate analytical findings to non-technical stakeholders clearly and impactfully.

Skills: catboost,lightgbm,predictive modelling,xgboost,data science,python