Senior Data Scientist
- Collaborate with robotics and automation specialists, mechanical and quality engineers to apply machine learning to industrial problems and situations
Seek opportunities in the production and development processes to utilize deep learning, algorithms and other machine learning tools for improvements
Implementation of machine learning (ML) and operations research (OR) tools, such as classical regression, classification, as well as neural networks and various optimization models for a wide range of prescriptive/predictive applications in dynamic production environments
Develop a toolkit to guide application of machine learning tools combined with statistical tools for common engineers
Assemble large data sets for analysis either through direct SQL-based querying or development of scripts and code-modules to collate distributed and disparate data sources
Analyze huge amounts of data-identifying anomalies (pattern detection) and variabilities in a measure of interest
Develops software components in Python, R and/or C/C++/ Objective-C towards roll-out of a data automation system Qualifications
- 5+ years of shown hands-on experience with design, implementation and application of ML/AI/Deep Learning and OR solutions and techniques to build models that solve real problems.
3+ years hands-on experience in optimization modeling, simulation and analysis with Python or Matlab.
Experience analyzing machine data (sensors, downtime log, machine states, etc) for IoT & predictive maintenance applications.
Experience applying deep learning frameworks, such as PyTorch/ Torch, TensorFlow, Keras to real-world applications that solve problems.
Knowledge of validated approaches for scale-ability, productionalizing models and implementing machine learning applied to expansive and diverse datasets (storage GPUs, techniques for deep learning at scale).
Strong software development skills with proficiency in Python.
Experienced user of machine learning and statistical-analysis libraries, such as GraphLab Create, scikit-learn, scipy, and NLTK.
High level of autonomy and influence to remove roadblocks and deliver results (evaluate and solve complex problems involving various teams ranging from data instrumentation to analytics tool development). A proven track record for self-study and self-exploration into new tools and techniques.
Ability to explain and present analyses machine learning concepts to a broad technical audience.
Experience with image processing, Computer Vision, and using ML tools to identify patterns in images, specifically applied to industrial or manufacturing environments is a plus.
Applied background in Hadoop, Spark, Hive, Cassandra, and knowledge of R is a plus.
Experience in data analytics for manufacturing problems is a plus.
Master’s or PhD degree in Computer Science, Math, Statistics, Physics, Engineering or related level of experience required.
- Opportunity to work on bleeding-edge projects
- Work with a highly motivated and dedicated team
- Flexible schedule
- Medical insurance
- Benefits program
- Corporate social events
- Professional development opportunities
Grid Dynamics is the engineering services company known for transformative, mission-critical cloud solutions for retail, finance and technology sectors. We architected some of the busiest e-commerce services on the Internet and have never had an outage during the peak season. Founded in 2006 and headquartered in San Ramon, California with offices throughout the US and Eastern Europe, we focus on big data analytics, scalable omnichannel services, DevOps, and cloud enablement.
Don’t see the right opportunity?Contact us anyway and let’s talk! To apply, send your resume and cover letter to moc.scimanyddirg@sboj
Grid Dynamics is an equal opportunity employer. We are committed to creating an inclusive environment for all employees during their employment and for all candidates during the application process. All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on, age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. All employment is decided on the basis of qualifications, merit, and business need.