Company:
Saviance Technologies
Location: Cambridge
Closing Date: 01/11/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
Senior Data Science Engineer
Location: Boston, MA- Onsite
Duration - Full Time
About BigRio: BigRio is a remote-based, technology consulting firm with headquarters in Boston, MA. We deliver solutions ranging from: custom development, software implementation, data analytics, and machine learning/AI integrations. We are a one-stop shop that attracts clients from a variety of industries because of our proven ability to deliver cutting-edge and cost-conscious software solutions.
With extensive domain knowledge, BigRio has teams of data architects, data engineers, software engineers, web developers, and consultants who deliver best-in-class solutions across a variety of verticals. Our diverse industry exposure equips us with invaluable tools, tricks, and techniques to tackle complex software and data challenges.
About Job: As a Senior Data Science Engineer, you will focus on leveraging radar data to drive strategic decisions and uncover actionable insights. You will design and implement data pipelines, clean and transform radar signals, and conduct exploratory data analysis for target detection, tracking, and classification. Additionally, you'll develop predictive models, integrate radar data with other sources, and collaborate closely with DSP and Client engineers to ensure seamless integration of radar processing algorithms.
Key Responsibilities:
Data Pipeline Development: Design and implement robust data pipelines tailored to radar data, including the processing, cleaning, and transformation of raw radar signals.
Exploratory Data Analysis: Conduct exploratory data analysis to extract insights specific to radar data, focusing on target detection, tracking, and classification.
Data Visualization: Explore, visualize, and identify patterns, trends, and relationships within radar data, providing actionable insights to stakeholders through publication-quality visualizations.
Predictive Modeling: Develop predictive models to support business initiatives, integrating radar data with other data sources for comprehensive solutions.
Collaboration: Work closely with DSP and Client engineers to ensure the seamless integration of radar data processing algorithms into existing systems.
Industry Knowledge: Stay current with industry trends and best practices in radar data analysis, continuously enhancing the organization's capabilities.
Communication: Clearly communicate technical concepts and progress across teams, ensuring alignment with broader company goals.
Documentation: Develop and maintain documentation for design specifications, test plans, and user manuals.
Technical Requirements:
Proficiency in programming languages such as Python, R, or Matlab.
Experience with radar data processing techniques and tools.
Strong understanding of statistical methods and machine learning algorithms.
Fluency in data science tools like NumPy/Scikit-learn and cloud services such as Google Cloud Platform.
Experience with automation processes for repetitive tasks and high-compute time activities.
Solid understanding of software development methodologies and version control systems.
Strong analytical and problem-solving skills with a focus on system-level performance optimization.
Excellent written and verbal communication skills.
Ability to work effectively both independently and within a team environment.
Preferred Qualifications:
Knowledge of RF engineering principles and practices.
Experience with radar hardware and systems.
Familiarity with radar data visualization techniques and tools, such as waterfall plots, range-Doppler maps, or ParaView.
Understanding of radar-specific data formats and protocols.
Experience with radar data simulation and modeling.
Machine learning experience, particularly in applying Client techniques to radar signal processing tasks.
Experience with radar-to-image projection, image segmentation, video object detection, or target detection in radar signals.
Proficiency in implementing and optimizing data augmentation techniques to enhance model performance and robustness.
Personal Qualities:
Strong interpersonal skills, with a passion for building camaraderie and working towards challenging goals with diverse collaborators.
Self-awareness of your strengths and the humility to leverage others' expertise in a team of specialists.
Respect and empathy to support company and team goals, fostering trust and safe collaboration.
A relentless work ethic and determination to achieve success, recognizing that time-to-market is crucial.
A lifelong learning mindset, with a drive to constantly improve your work and yourself.
Courage to move fast, innovate, and ship impactful products.
Exceptional communication skills, with a focus on clear, comprehensive, and precise information sharing to ensure alignment across teams.
Education and Experience:
A Master's or Ph.D. in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related field.
8+ years of relevant experience in data science.
Hands-on experience in commercial settings with a proven track record of success.
Full life cycle experience with an electronics product that has achieved commercial success is highly desirable.
Preference for candidates with experience in startups or fast-paced environments, particularly those with exposure to ambient sensing and sensor fusion technologies.
Location: Boston, MA- Onsite
Duration - Full Time
About BigRio: BigRio is a remote-based, technology consulting firm with headquarters in Boston, MA. We deliver solutions ranging from: custom development, software implementation, data analytics, and machine learning/AI integrations. We are a one-stop shop that attracts clients from a variety of industries because of our proven ability to deliver cutting-edge and cost-conscious software solutions.
With extensive domain knowledge, BigRio has teams of data architects, data engineers, software engineers, web developers, and consultants who deliver best-in-class solutions across a variety of verticals. Our diverse industry exposure equips us with invaluable tools, tricks, and techniques to tackle complex software and data challenges.
About Job: As a Senior Data Science Engineer, you will focus on leveraging radar data to drive strategic decisions and uncover actionable insights. You will design and implement data pipelines, clean and transform radar signals, and conduct exploratory data analysis for target detection, tracking, and classification. Additionally, you'll develop predictive models, integrate radar data with other sources, and collaborate closely with DSP and Client engineers to ensure seamless integration of radar processing algorithms.
Key Responsibilities:
Data Pipeline Development: Design and implement robust data pipelines tailored to radar data, including the processing, cleaning, and transformation of raw radar signals.
Exploratory Data Analysis: Conduct exploratory data analysis to extract insights specific to radar data, focusing on target detection, tracking, and classification.
Data Visualization: Explore, visualize, and identify patterns, trends, and relationships within radar data, providing actionable insights to stakeholders through publication-quality visualizations.
Predictive Modeling: Develop predictive models to support business initiatives, integrating radar data with other data sources for comprehensive solutions.
Collaboration: Work closely with DSP and Client engineers to ensure the seamless integration of radar data processing algorithms into existing systems.
Industry Knowledge: Stay current with industry trends and best practices in radar data analysis, continuously enhancing the organization's capabilities.
Communication: Clearly communicate technical concepts and progress across teams, ensuring alignment with broader company goals.
Documentation: Develop and maintain documentation for design specifications, test plans, and user manuals.
Technical Requirements:
Proficiency in programming languages such as Python, R, or Matlab.
Experience with radar data processing techniques and tools.
Strong understanding of statistical methods and machine learning algorithms.
Fluency in data science tools like NumPy/Scikit-learn and cloud services such as Google Cloud Platform.
Experience with automation processes for repetitive tasks and high-compute time activities.
Solid understanding of software development methodologies and version control systems.
Strong analytical and problem-solving skills with a focus on system-level performance optimization.
Excellent written and verbal communication skills.
Ability to work effectively both independently and within a team environment.
Preferred Qualifications:
Knowledge of RF engineering principles and practices.
Experience with radar hardware and systems.
Familiarity with radar data visualization techniques and tools, such as waterfall plots, range-Doppler maps, or ParaView.
Understanding of radar-specific data formats and protocols.
Experience with radar data simulation and modeling.
Machine learning experience, particularly in applying Client techniques to radar signal processing tasks.
Experience with radar-to-image projection, image segmentation, video object detection, or target detection in radar signals.
Proficiency in implementing and optimizing data augmentation techniques to enhance model performance and robustness.
Personal Qualities:
Strong interpersonal skills, with a passion for building camaraderie and working towards challenging goals with diverse collaborators.
Self-awareness of your strengths and the humility to leverage others' expertise in a team of specialists.
Respect and empathy to support company and team goals, fostering trust and safe collaboration.
A relentless work ethic and determination to achieve success, recognizing that time-to-market is crucial.
A lifelong learning mindset, with a drive to constantly improve your work and yourself.
Courage to move fast, innovate, and ship impactful products.
Exceptional communication skills, with a focus on clear, comprehensive, and precise information sharing to ensure alignment across teams.
Education and Experience:
A Master's or Ph.D. in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related field.
8+ years of relevant experience in data science.
Hands-on experience in commercial settings with a proven track record of success.
Full life cycle experience with an electronics product that has achieved commercial success is highly desirable.
Preference for candidates with experience in startups or fast-paced environments, particularly those with exposure to ambient sensing and sensor fusion technologies.
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