Senior Data Scientist

Competetive SalaryPF and GratuityAbout Our ClientOur client is an international professional services brand of firms, operating as partnerships under the brand. It is the second-largest professional services network in the worldJob DescriptionJob RequirementsEducation* Bachelor's degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)* Master's degree preferred (MBA/MS Computer Science/ Computer Science, etc.)Relevant Experience* 5 - 7 years for Data Scientist* Relevant working experience in a data science/advanced analytics roleBehavioural Skills* Delivery Excellence* Business disposition* Social intelligence* Innovation and agilityExperience* Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.)* Statistical modelling using Analytical tools (R, Python, KNIME, etc.)* Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)* Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference.* Practical experience deploying models using MLOps tools and practices (, MLflow, DVC, Docker, etc.)* Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.)* Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)* Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools* Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)* Microsoft Office applications (MS Excel, etc.)Roles & ResponsibilitiesAnalytics & Strategy1. Analyse large-scale structured and unstructured data; develop deep-dive analyses and machine learning models in retail, marketing, merchandising, and other areas of the business2. Utilize data mining, statistical and machine learning techniques to derive business value from store, product, operations, financial, and customer transactional data3. Apply multiple algorithms or architectures and recommend the best model with in-depth description to evangelize data-driven business decisions4. Utilize cloud setup to extract processed data for statistical modelling and big data analysis, and visualization tools to represent large sets of time series/cross-sectional dataOperational Excellence1. Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project2. Structure hypothesis, build thoughtful analyses, develop underlying data models and bring clarity to previously undefined problems3. Partner with Data Engineering to build, design and maintain core data infrastructure, pipelines and data workflows to automate dashboards and analysesStakeholder Engagement1. Working collaboratively across multiple sets of stakeholders - Business functions, Data Engineers, Data Visualization experts to deliver on project deliverables2. Articulate complex data science models to business teams and present the insights in easily understandable and innovative formatsThe Successful ApplicantJob RequirementsEducation* Bachelor's degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)* Master's degree preferred (MBA/MS Computer Science/ Computer Science, etc.)Relevant Experience* 5 - 7 years for Data Scientist* Relevant working experience in a data science/advanced analytics roleBehavioural Skills* Delivery Excellence* Business disposition* Social intelligence* Innovation and agilityExperience* Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics, etc.)* Statistical modelling using Analytical tools (R, Python, KNIME, etc.)* Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference)* Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference.* Practical experience deploying models using MLOps tools and practices (, MLflow, DVC, Docker, etc.)* Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.)* Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.)* Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools* Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.)* Microsoft Office applications (MS Excel, etc.)Roles & ResponsibilitiesAnalytics & Strategy1. Analyse large-scale structured and unstructured data; develop deep-dive analyses and machine learning models in retail, marketing, merchandising, and other areas of the business2. Utilize data mining, statistical and machine learning techniques to derive business value from store, product, operations, financial, and customer transactional data3. Apply multiple algorithms or architectures and recommend the best model with in-depth description to evangelize data-driven business decisions4. Utilize cloud setup to extract processed data for statistical modelling and big data analysis, and visualization tools to represent large sets of time series/cross-sectional dataOperational Excellence1. Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project2. Structure hypothesis, build thoughtful analyses, develop underlying data models and bring clarity to previously undefined problems3. Partner with Data Engineering to build, design and maintain core data infrastructure, pipelines and data workflows to automate dashboards and analysesStakeholder Engagement1. Working collaboratively across multiple sets of stakeholders - Business functions, Data Engineers, Data Visualization experts to deliver on project deliverables2. Articulate complex data science models to business teams and present the insights in easily understandable and innovative formats