Data Scientist

Data Scientist Data Scientist role to develop and deliver analytics models for Client's equipment condition monitoring for the enterprise, and for aftermarket solutions for customers and dealers. Condition monitoring models include failure prediction, remaining life estimation, service interval extension, and component risk models. Methods include machine learning, deep learning, statistical and rule-based models, and other data analytics techniques to generate actionable insights from time-series machine sensor data, other telematics data, fluids analysis, and machine inspection and service records. Responsibilities: Collect and negotiate requirements for condition monitoring models. Access, analyze, cleanse, preprocess data; cultivate ground truth data sets as needed. Explore and downselect modeling approaches. Develop, backtest and validate models in python, in both on-prem and AWS environments. Compute model performance metrics. Participate in daily standups and sprint reveals in Scrum/Agile environment. Explain and defend modeling decisions and performance results. Support model in production, resolve incident tickets. Technical Skills Required: Excellent python skills (numpy/pandas/matplotlib/sklearn), version control (git), SQL and database APIs (cx_oracle, pymysql, sqlalchemy), cloud deployment experience (AWS, containerization) and familiarity with AWS services (S3/EC2/SageMaker). Comfortable and effective working in an Agile/Scrum environment. Desired qualifications: Machine Learning model development experience, familiarity with engineering/IOT systems, telematics/timeseries data analysis, and multiprocessing frameworks (dask, pyspark). Desired Skills: AWS Certified Cloud Practitioner (or higher) - desired Soft Skills Required: Excellent communication skills. Critical thinking and independent problem resolution. Ability to work both independently and on a team: collaborates and compromises effectively. Samprasoft