Manager Data Scientist

Key Skills

Aartificial intelligence, Agile methodologies, Apache Hadoop, Apache Hive, C Programming, C++, Data science techniques, Deep Learning, Effective communication skills, English Proficiency, ETL frameworks, German Language, GoLang, JIRA, Jupyter Notebook, Linux Operating system, Machine learning techniques, MLOps tools, Pandas, PowerBI, Predictive Modeling, Presentation skills, Python Programming, PyTorch, R Programming, Reinforcement Learning, SAS, Scikit-learn, Spark Core, SQL, Stata, Statistics, Tableau, TensorFlow, Transformer, Unix Operating system

Job Description

Job Description And Responsibilities

• Minimum of 6+ years of analytics expertise in applying statistical solutions to business problems
• Team oriented, collaborative, diplomatic, and agile working style
• Post-graduate degree (Masters or PhD) in a Quantitative field such as Statistics, Mathematics, Operational Research, Computer Science, Economics, Engineering, or equivalent
• Must have experience with Hadoop, SQL, Spark/Pyspark and Python
• Build or have knowledge of ETL pipelines in Spark, Python, HIVE that process transaction and account level data and standardize data fields across various data sources
• Analyzing large data sets using programming languages such as Python, R, SQL and/or Spark
• Building predictive and descriptive statistical models using machine learning tool kit, Jupyter notebooks, Python, and/or SAS
• Experience in the application of descriptive analytics, predictive modelling, and machine learning technique to business problems
• Experience planning, organizing, and leading end to end projects with diverse cross-functional teams
• Experience planning, organizing, and managing multiple large projects with diverse cross-functional teams
• Demonstrated ability to incorporate new techniques to solve business problems
• Demonstrated resource planning and delivery skills

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.