| Only USC and GC Role : Sr. Data Scientist (Radar, DSP, RF Exp Required) , Boston, MA at Boston, Massachusetts, USA |
| Email: [email protected] |
| Role : Sr. Data Scientist (Radar, DSP, RF Exp Required) Location: Boston, MA Visa: USC and GC As a Senior Data Science Engineer at Cherish, your primary focus will be on harnessing the power of radar data to drive strategic decision-making and unlock actionable insights. Working alongside cross-functional teams, you'll leverage your expertise in statistical analysis and data modeling to uncover hidden patterns and trends within the radar-generated datasets. Your role will involve designing and implementing robust data pipelines tailored to the unique characteristics of radar data, including processing, cleaning, and transforming raw radar signals into actionable insights. You'll conduct exploratory data analysis to extract valuable insights specific to radar data, such as target detection, tracking, and classification. Additionally, you'll develop predictive models to support key business initiatives, integrating radar data with other data sources to provide comprehensive solutions. Collaborating closely with our DSP engineers and ML engineers, you'll ensure seamless integration of radar data processing algorithms into existing systems. With your keen eye for detail and advanced analytical skills, you'll play a pivotal role in shaping the future of our data-driven organization, powered by radar technology Your Superpowers You describe yourself as an innovative engineer who blends technical mastery with visionary thinking. Renowned for digging deep across data sets spanning multiple layers of dimensionality, you are hungry to find patterns and trends where others see none. Your inventive approach yields groundbreaking solutions, collaborating effectively to engineer optimal outcomes. The Jobs Responsibilities As a collaborative subject-matter expert (SME) on a Team of SMEs, you will use your superpowers (listed above) to collaborate with others with their superpowers (youll work with others who excel at business strategy, product management, user experience and industrial design, electronics design and engineering, software architecture and development, supply chain and logistics management, finance and business modeling, SCRUM and program management, business development and contracting, sales, and marketing) in a supportive and safe team setting to achieve company goals. You will be responsible for: Design and implement robust data pipelines tailored to radar data, including processing, cleaning, and transforming raw radar signals. Conduct exploratory data analysis to extract valuable insights specific to radar data, such as target detection, tracking, and classification. Explore and visualize data to identify patterns, trends, and relationships, providing actionable insights to stakeholders. Craft publication-quality data visualizations highlighting results and improvements Develop predictive models to support key business initiatives, integrating radar data with other data sources to provide comprehensive solutions. Collaborate closely with DSP and ML engineers to ensure seamless radar data processing algorithms integration into existing systems. Stay current with industry trends and best practices in radar data analysis, continuously enhancing the organization's capabilities in this domain. Clearly communicate technical concepts and progress not only within your team but also to other teams across the company. Ensure that all departments understand the work that you are doing and how it aligns with and supports the broader company goals. Develop and maintain documentation for design specifications, test plans, and user manuals. Stay up-to-date with the latest advancements in data science methodologies and technologies. Key Technical Requirements : To hit the ground running, you are comfortable across the entire engineering life cycle from system design to algorithm development to system testing and optimization, leading to a successful product launch. In particular: 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 (Google Cloud Platform). Implementing 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 in a team environment. In addition, While not essential, it is a definite plus if: You know RF engineering principles and practices. You have experience with radar hardware and systems. You know radar data visualization techniques and tools, such as waterfall plots, range-Doppler maps, or ParaView Familiarity with radar-specific data formats and protocols. You have experience with radar data simulation and modeling. You have machine learning experience, particularly in applying ML techniques to radar signal processing tasks. You have experience with one or more of the following: radar-to-image projection, image segmentation, video object detection, or target detection in radar signal Experience implementing and optimizing data augmentation techniques (e.g., image flipping, rotation, scaling, filtering, text synonym replacement, SMOTE) to enhance model performance and robustness. Personal Qualities Wed love you to be self-aware, thoughtful, empathetic, diligent, hard-working, a lifelong learner, and a great team player. Youd show us that you have: Strong interpersonal skills and the ability, perhaps even a passion, to build camaraderie and work effectively on difficult goals with a broad range of business and technical collaborators across cultures and skills. Self-awareness to know your own superpower (nobody is great at all things) and the humility to permit others to exercise theirs on a team of accomplished specialists Respect and empathy to recognize and support the goals of the company, your team, and colleagues in ways that build trust for people to feel safe to disagree and commit (The Amazon Way) A work ethic that doesnt quit, that recognizes that time-to-market is often the only thing that separates teams that win from those that dont (No matter how hard you work, someone else is working harder. Elon Musk) Tenacity and a dogged determination to never give up Innate hunger to constantly do better and evolve both your work product and yourself (Youre a lifelong learner) The courage to move fast, break things, and ship products that people use (Real artists ship. Steve Jobs) Exceptional communication skills characterized by meticulous attention to detail and precision in verbal and written expression. Consistently deliver clear, comprehensive, and precise information to ensure all team members are aligned and well-informed. Additionally, articulate the team's efforts and impact on other teams, cultivating close collaboration to achieve company-wide objectives. Education and Experience A Master's or PhD degree in Computer Science, Electrical Engineering, Statistics, Mathematics, or a related field. 8+ years of relevant experience in data science. Real-world work experience in relevant roles in a commercial setting. Ideally, full life cycle experience with an electronics product that has shipped and achieved meaningful commercial success. Preference for candidates with experience in a startup or fast-paced environment and exposure to ambient sensing and sensor fusion technologies. Thanks & Warm Regards, Alok Singh | Technical Recruiter TekNavigators Staffing 978-558-4666 *109 Alok @tek-staffing.com tek-staffing.com linkedin.com/in/alok-singh-8900bb210 -- Keywords: machine learning rlang information technology green card Massachusetts Only USC and GC Role : Sr. Data Scientist (Radar, DSP, RF Exp Required) , Boston, MA [email protected] |
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| Wed Aug 28 20:05:00 UTC 2024 |