Data Science Engineer

Job Description

As a Data Scientist at our company, your role will involve the following key responsibilities:- Researching and developing production-grade models (forecasting, anomaly detection, optimization, clustering, etc.) for global cloud business by using statistical and machine learning techniques.- Managing large volumes of data, and creating new and improved solutions for data collection, management, analyses, and data science model development.- Driving the onboarding of new data and the refinement of existing data sources through feature engineering and feature selection.- Applying statistical concepts and cutting-edge machine learning techniques to analyze cloud demand and optimize data science model code for distributed computing platforms and task automation.- Working closely with other data scientists and data engineers to deploy models that drive cloud infrastructure capacity planning.- Presenting analytical findings and business insights to project managers, stakeholders, and senior leadership.- Keeping abreast of new statistical / machine learning techniques and implementing them as appropriate to improve predictive performance.- Overseeing the analysis of data and leading the team in identifying trends, patterns, correlations, and insights to develop new forecasting models and improve existing models.- Leading collaboration among the team and leveraging data to identify pockets of opportunity to apply state-of-the-art algorithms to improve a solution to a business problem.- Consistently leveraging knowledge of techniques to optimize analysis using algorithms.- Modifying statistical analysis tools for evaluating Machine Learning models.- Providing coaching to team members on business context, interpretation, and the implications of findings.- Interpreting findings and their implications for multiple businesses.- Championing methodological rigour by calling attention to the limitations of knowledge wherever biases in data, methods, and analysis exist.- Generating and leveraging insights that inform future studies and reframe the research agenda.- Informing current business decisions by implementing and adapting supply-chain strategies through complex business intelligence.Qualifications required for this role include:- M.Sc. in Statistics, Applied Mathematics, Applied Economics, Computer Science or Engineering, Data Science, Operations Research or similar applied quantitative field.- 7 years of industry experience in developing production-grade statistical and machine learning code in a collaborative team environment.- Prior experience in machine learning using R or Python (scikit / numpy / pandas / statsmodel).- Prior experience in time series forecasting.- Prior experience with typical data management systems and tools such as SQL.- Knowledge and ability to work within a large-scale computing or big data context.- Hands-on experience with Hadoop, Spark, DataBricks or similar.- Excellent analytical skills.- Ability to understand business needs and translate them into technical solutions.- Experience with deep learning models (e.g., tensorflow, PyTorch, CNTK) and solid knowledge of theory and practice.- Practical and professional experience contributing to and maintaining a large code base with code versioning systems such as Git.- Creative thinking skills with emphasis on developing innovative methods to solve hard problems under ambiguity.- Good interpersonal and communication (verbal and written) skills.This is a challenging yet rewarding opportunity for a skilled Data Scientist to contribute to cutting-edge projects in a dynamic environment. As a Data Scientist at our company, your role will involve the following key responsibilities:- Researching and developing production-grade models (forecasting, anomaly detection, optimization, clustering, etc.) for global cloud business by using statistical and machine learning techniques.- Managing large volumes of data, and creating new and improved solutions for data collection, management, analyses, and data science model development.- Driving the onboarding of new data and the refinement of existing data sources through feature engineering and feature selection.- Applying statistical concepts and cutting-edge machine learning techniques to analyze cloud demand and optimize data science model code for distributed computing platforms and task automation.- Working closely with other data scientists and data engineers to deploy models that drive cloud infrastructure capacity planning.- Presenting analytical findings and business insights to project managers, stakeholders, and senior leadership.- Keeping abreast of new statistical / machine learning techniques and implementing them as appropriate to improve predictive performance.- Overseeing the analysis of data and leading the team in identifying trends, patterns, correlations, and insights to develop new forecasting models and improve existing models.- Leading coll

Keyskills :
Statistical AnalysisMachine LearningForecastingAnomaly DetectionOptimizationClusteringData ManagementFeature SelectionSQLHadoopSparkDeep LearningGitFeature EngineeringData Science Model DevelopmentTime Series ForecastingDataBricksTensorFl