Data Scientist

• Preferred education qualifications: Bachelor/ Master's degree in Statistics, Operation Research, Computer Science, Data Science OR related quantitative field.
• Geography: SAPMENA

Job objectives:

• Design, 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 description:

• Deep 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/skills:

• 5+ 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.