[BT NA SAPMENA] Data Scientist

Data ScientistPreferred education qualifications: Bachelor/ Master's degree in Statistics, Operation Research, Computer Science, Data Science OR related quantitative field.Geography: SAPMENAJob ObjectivesDesign, develop, implement, and maintain data science and machine learning solutions to meet enterprise goals. Collaborate with cross-functional teams to leverage statistical modeling, machine learning, and data mining techniques to improve forecast accuracy and aid strategic decision-making across the organization. Scale the proven AI-ML Product across the SAPMENA region.Job DescriptionDeep understanding of business/functional needs, problem statements and objectives/success criteria.Develop and maintain sophisticated statistical forecasting models, incorporating factors such as seasonality, promotions, media, traffic and other economic indicators.Collaborate with internal and external stakeholders including business, data scientists & product team to understand the business and product needs and translate them into actionable data-driven solutions.Review MVP implementations, provide recommendations and ensure Data Science best practices and guidelines are followed.Evaluate and compare the performance of different forecasting models, recommending optimal approaches for various business scenarios.Analyze large and complex datasets to identify patterns, insights, and potential risks and opportunities.Communicate forecasting results and insights to both technical and non-technical audiences through clear visualizations and presentations.Stay up to date with the latest advancements in forecasting techniques and technologies, continuously seeking opportunities for improvement.Contribute to the development of a robust data infrastructure for AI-ML solutions, ensuring data quality and accessibility.Collaborate with other data scientists and engineers to build and deploy scalable AI-ML solutions.Preferred Profile/skills5+ years in developing and implementing forecasting models.Proven track record in data analysis (EDA, profiling, sampling), data engineering (wrangling, storage, pipelines, orchestration).Proven expertise in time series analysis, regression analysis, and other statistical modelling techniques.Experience in ML algorithms such as ARIMA, Prophet, Random Forests, and Gradient Boosting algorithms (XGBoost, LightGBM, CatBoost).Experience in model explainability with Shapley plot and data drift detection metrics.Strong programming & analysis skills with Python and SQL, including experience with relevant forecasting packages.Prior experience on Data Science & ML Engineering on Google Cloud.Proficiency in version control systems such as GitHub.Strong organizational capabilities; and ability to work in a matrix/ multidisciplinary team.Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical audience.Experience in Beauty or Retail/FMCG industry is preferred.Experience in handling large volume of data (>100 GB).Experience in delivering AI-ML projects using Agile methodologies is preferred.Proven ability to work proactively and independently to address product requirements and design optimal solutions.