Data Scientist

Are you passionate about transforming vast amounts of data into actionable insights? We're seeking a Data Scientist to join our innovative team and help shape the future of data-driven solutions. You'll collaborate closely with our client's Product team, designing and launching reliable, high-efficiency data pipelines that analyze and model data from complex, large-scale datasets. This role requires a systematic thinker with the ability to communicate effectively across various technical environments.

The ideal candidate is someone who thrives on uncovering insights within massive datasets while ensuring the architecture, reliability, efficiency, and quality of data processes are top-notch. As we continuously release new features and products, you'll be expected to design and maintain robust, system-level data architectures.

In this role, you'll have the opportunity to bring data to life-transforming raw information into intuitive analytics that open new doors for our customers. If you have an inquisitive and innovative mindset, this could be the perfect fit for you!

Key Responsibilities:

• Discover and work with new datasets that enhance solution development
• Data curation, evaluation, and analysis
• Design, build, and implement quantitative models
• Perform validation and quality assurance on data, models, and results
• Collaborate with the product team to deploy and implement data solutions
• Address current and upcoming user needs based on customer feedback
• Approach tasks from a systems-level perspective, integrating your solutions into broader projects

Qualifications:

• Active Secret, TS, or TS/SCI clearance
• Strong academic background in Statistics, Mathematics, Engineering, or a related field (Master's degree preferred)
• Proficiency in Python, especially with data libraries like Pandas and PyArrow
• Experience in database management (MySQL, Oracle) and large-scale data processing
• Experience in implementing batch processing pipelines in high-performance computing (HPC) or cloud environments
• Familiarity with cloud platforms such as AWS, GCloud, or Azure is a plus