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Senior Data Scientist
REC10021671
Remote / Telework
Updated 18h ago
Fees
10% of Salary
My fee % [?]
70.0%
Positions
1
Type
Direct Hire
Salary
$100,000 - $150,000/year
My new applicants
0
My candidates
submitted
0
Total invited candidates
18
Total active candidates
2
Recruiters engaged
S
Pic
S
Pic
Pic
5+
Industry
Information Technology
Category
Scientific
Education
Doctoral Degree
Experience
5-7 years
Travel
Never
Relocation assistance
-
Work eligibility
Green Card ,US Citizen
Job description
We are committed to building a culturally diverse environment where differences are valued and respected. Women, minorities, individuals with disabilities, veterans, and intersectional individuals are highly encouraged to apply.



Here is an opportunity to join our company, a company whose solutions lie at the convergence of many exponentially accelerating innovative technologies: Cloud, edge computing and the Industrial Internet of Things (IoT); AI, machine learning and deep learning; Big Data and analytics; and 3D printing (additive manufacturing). Our company helps customers lower the costs of designing, operating, and sustaining their high value mechanical assets by providing digital twin technology that predicts the life of mechanical systems.

The company's DigitalClone® SaaS solutions use proprietary algorithms derived from physics-based modeling and machine learning. Help us achieve our vision of a world where rotorcraft manufacturers, wind energy operators and railroads rely on company DigitalClone for a digital implementation of their O&M cost reduction strategy. And a high concentration of PhDs will keep you intellectually stimulated and challenged.



Position Summary:

The Senior/Lead Data Scientist leads efforts to expand the data science capabilities of our company's cloud-based predictive analytics platform. The individual in this position will have a solid background in production-level machine learning systems with broad exposure to a wide variety of algorithmic techniques (demonstrable proof of impactful work in areas such as damage-anomaly detection, natural language processing, explainability-driven deep learning and time-series forecasting is valuable). Our team particularly values experience in building inferential algorithms for high-stake decisions while dealing with noisy, diverse, distributed datasets. Being able to communicate complex concepts in simple language to diverse stakeholders with an unwavering commitment to empathy and customer obsession is highly desired. The title and associated responsibility for the position can be modified for the right candidate – if our mission inspires you, please apply for this position.



Responsibilities:

· Building and Implementing the machine learning based statistical models to predict certain damage modes in major components in wind turbines such as Gearbox.

· Reviews large data sets (SCADA) of sensor-derived observations and alarm logs from operating wind turbines and utilizes subject matter expertise to ascertain veracity of these data

· Develops, implements and tests statistical algorithms for anomaly detection in large datasets from fleets of field-operating large machines e.g. wind turbines and rotorcraft

· Lead and mentor junior team members in design, optimization and production-deployment of machine learning and statistical forecasting models while adhering to timelines governed by the product development roadmap

· Interface with customer-facing executives to stay abreast with voice of the customer and update technical roadmap accordingly.



Experience & Qualifications:

Masters or Ph.D. in mechanical engineering, industrial engineering, wind energy systems, aerospace engineering, statistics, data science, computer science, or related discipline
Candidates MUST HAVE renewable energy industry experience for consideration
Demonstrable knowledge of theory and application of (one or more) techniques across supervised/unsupervised learning, natural language processing, computer vision and statistical inference
Demonstrated experience working with large (TB+) repositories of structured and unstructured data spanning forms such as numeric, text, images/rasters
Familiar with some form of physics-based modeling, such as FEM, CFD, MD, MC, DFT, etc.
Proficiency working with a modern programming language focused on data analysis and machine learning (e.g. Python, R, Julia, Matlab)
Understanding/familiarity with deploying, monitoring and retraining machine learning models in cloud-facing production setting (AWS preferred)
Proficiency with relevant tools and libraries for a collaborative machine learning workflow: scikit-learn, git etc.
Knowledgeable in programmatically consuming data from APIs and other micro-services
Possess a curious mind, insatiable drive to learn proactively and profound humility and empathy for your colleagues as well the customer
US citizenship required