Data Scientist

Where You Come In:

We are currently seeking a Data Scientist to join our growing team! At KCF, you will operate as part of a cross-functional squad with other engineers (Software, Hardware, DevOps, and Machine Learning). As a Data Scientist, you will help to build and maintain KCF’s SMARTdiagnostics machine health platform, which stores and processes industrial IoT sensor data to provide analytics and insights to our users. This will help us achieve our goal of zero waste, zero downtime, and zero safety incidents for all of industry.

This role can be 100% remote-based. With our Work From Home, Work From Anywhere model, KCF employees are spread across 27 different U.S states. We advocate for owning your work - you define how you do it and where you do it.  Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.

This is starting to sound like your next challenge, right? Read on for more info!

Essential Functions:

• Utilize statistical analysis, machine learning, and data mining techniques to extract insights from large datasets.
• Clean, preprocess, and manipulate data to ensure its quality, accuracy, and usability for analysis.
• Develop and implement predictive models, algorithms, and analytical solutions to solve complex business problems.
• Evaluate the effectiveness of existing features, and aid in the development of new features for the purpose of predictive modeling.
• Assess the performance of machine learning models using various evaluation metrics and validation techniques to ensure robustness and reliability of models.
• Present data insights in a compelling and understandable manner to both technical and non-technical stakeholders through visualizations, reports, and presentations.
• Ensure compliance with data privacy regulations and ethical standards in data handling while implementing governance practices to maintain data integrity and security.
• Design and conduct hypothesis testing to validate assumptions and assess the impact of changes or new features within the product.
• Collaborate with domain experts, engineers, and other teams to understand business needs, gather domain-specific knowledge, and integrate diverse perspectives into data-driven solutions.
• Prioritize continuous learning and remaining at the forefront of the field by staying up-to-date with the latest advancements in data science, exploring new techniques, algorithms, and tools.
• Optimize existing algorithms and processes for efficiency, scalability, and performance in handling large-scale datasets and real-time applications.
• Analyze customer behavior patterns, market trends, and provide insights to help drive strategic decision-making and product enhancements.
• Other duties as assigned by the supervisor and other KCF leadership staff 

Qualifications: 

• Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
• MSc or PhD in Statistics, Machine Learning, Computer Science, or equivalent preferred
• 3+ years of Applied ML experience; experience within the manufacturing domain, model development for IoT applications, and time series analysis preferred.
• Experience with Bayesian methods, regression analysis, and other statistical techniques for predictive modeling.
• Strong background in data visualization and ability to communicate complex data insights effectively.
• Familiarity with a variety of machine learning techniques and their real-world advantages/drawbacks, as well as experience in implementing, validating, and optimizing AI models.
• Demonstrated expertise in Python for developing and implementing machine learning algorithms and models.
• Experience working with AWS, Google Cloud, or other cloud-based solutions to train models, set up data pipelines, and set up inference engines
• Proficiency in microservices and deployment of ML models is preferred
• Familiarity with tools such as AWS Sagemaker, Hadoop, Spark, Data Bricks is preferred
• Understanding/Knowledge of the following concepts: feature stores, data lineage, A/B testing, model scoring/feedback
• Experience in applying digital signal processing techniques such as Fourier transforms, filtering and wavelet analysis to time series data is preferred.
• Knowledge of concurrent programming such as threads and asynchronous I/O is preferred.