Data Scientist

WHAT CANDIDATE 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 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  

• Work experience of 5+ 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 Data ScientistPython skills, incl. pandas, Numpy, scikit-learn, SciPy, stats models 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 cat boost).
• 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.