Job Profile Summary 

Produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. Apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement. Able to frame Data Science problems, put mathematical models into production, writes reusable code, builds high quality data pipelines in cloud environments and answer business questions to management. Requires in-depth conceptual and practical knowledge in own job discipline and basic knowledge of related job disciplines. Solves complex problems. Works independently, receives minimal guidance. May lead projects or project steps within a broader project or may have accountability for on-going activities or objectives. Acts as a resource for colleagues with less experience. Level at which career may stabilize for many years or until retirement.

Responsibilities

• Uses best practices, experience and knowledge of internal or external business issues to improve products or services.
• Typically resolves complex problems or problems where precedent may not exist.
• May lead the work of small project teams, providing guidance to colleagues with less experience.
• He has a good intuition about the inner workings of statistical models and how to implement them.
• At this level Data scientists need to interpret the results of their analyses, and then simplify and synthesize them.
• Decisions impact the quality, efficiency and effectiveness of own team.
• May impact closely related teams through quality of output and service provided.
• Adopts and implements business and process improvements.
• Works on complex problems of diverse scope where analysis of data requires evaluation of identifiable factors.
• Demonstrates good judgment in selecting methods and techniques for obtaining solutions.
• Networks with internal and external contacts; recognizes the importance of relationships outside of specialty field.
• May provide consultation with internal GDO and external contacts.

Knowledge

• Engineering complex product solutions.
• Influencing decisions requires the ability to use data to tell a clear, compelling story.
• Requires general understanding of the processes, procedures and systems used to accomplish the work and familiarity with the broader underlying concepts in own job family/job discipline.
• Applies understanding of how the team relates to other closely related areas to improve efficiency of own work.
• Strong structured learning/hierarchical and statistical modeling techniques.
• Machine learning experience.
• Ability to obtain data from multiple, disparate data sources including structured, semi-structured and unstructured data.
• Experience with cloud-based ecosystems (GCP, AWS).
• Successful demonstrated experience in working on problems of diverse scope and complexity ranging from moderate to substantial in a collaborative fashion alongside other individuals or teams.
• Experience in creating reports, projections, models, and presentations to support business.
• Experience with agile software launching, Tensorflow experience, and/or working with data integration developers to assess data quality and define data processing business rules for cleansing, aggregation, enhancement, supporting analysis and predictive modelling activities.

Qualifications

• Bachelor’s Degree in Applied Mathematics, Physics, or Quantitive Discipline, Master’s degree on Data science, business analytics, or other data related field.
• At least 4+ years of relevant technical experience, including at least 3 years of data related exposure. Experience creating solutions deployed.