Data Scientist III at SparkCognition
Qualified candidates are deeply analytical with a keen understanding of the business processes and programs and the ability to translate data and insights. They will have a track record of driving successful data science initiatives for business and customer-facing outcomes.
This is a highly visible role that offers a significant professional development opportunity, as well as the opportunity to meaningfully contribute to SparkCognition’s success and that of its customers.
- Partner with other data scientists and project teams in developing and applying ML expertise in developing and delivering novel customer solutions
- Independently and effectively engage with external technical stakeholders and subject matter experts to understand and solve critical business problems through the application of cutting-edge artificial intelligence
- Design and deploy machine learning models for commercial and industrial applications, such as anomaly detection, prescriptive maintenance, and fraud detection
- Lead all phases of the data science process from data exploration and processing, feature selection and engineering, model training and testing, and information synthesis
- Maintain and apply deep understanding and application of all relevant SparkCognition products/technologies to support ongoing projects and proposal work
- Use and/or pioneer procedures and/or automated toolsets to more efficiently and effectively perform data science activities
- Contribute to AI product development and key data science research areas, internally and externally
- Strong understanding of Data Science, including basic elements of machine learning, statistics, probability, and modeling.
- Experience with Data Science programming languages, such as Python, R, Matlab
- Experience with machine learning frameworks, such as PyTorch, TensorFlow, Theano, and Keras.
- Applied knowledge of ML techniques/algorithms including linear models, neural networks, decision trees, Bayesian techniques, clustering, and anomaly detection
- Experience managing large volumes of data (terabytes or more)
- Experience with participating in and/or leading project teams, specifically data science teams
- Strong written and verbal communications, ability to translate complex technical topics to internal and external stakeholders
- Ability to form strong working relationships with team members, cross-departmentally, customers' technical teams, and executive leadership
- Degree in Computer Science, Statistics, Physics, Mathematics, Engineering, or a related scientific discipline
- Graduate or Doctorate degree (or equivalent experience) in one of the fields above
- Experience with distributed computing, such as Hadoop, Spark, or an MPP environment
- Experience with developing application on full stack of HTTP, JSON, REST, React, Java/C#, SQL and no-SQL databases
- Experience with Natural Language Processing