Lead Data Scientist

Description

We are seeking a highly motivated and talented Lead Data Scientist who will play a critical part in advancing research and development using cutting-edge data science techniques. You will support DI’s teams by providing expertise and technical products related to data science and engineering, including (but not limited to) time-series data processing, multimodal data modeling, algorithm development, anomaly detection, optimization models, tuning large language models, and advances in AI/ML.

THIS POSITION REQUIRES THE ABILITY TO OBTAIN AND MAINTAIN A UNITED STATES SECURITY CLEARANCE.

Primary Responsibilities:

Lead and mentor data scientist and machine learning engineers, fostering a culture of innovation and continuous learning

Provide regular feedback through one-on-one meetings, performance reviews, and coaching.

Collaborate with cross-functional teams, including product managers, designers, and stakeholders, to define project goals and technical requirements.

Ensure adherence to best practices, standards, and company policies.

Build and maintain models for various business problems and content recommendations.

Support the construction and implementation of data measurement frameworks to track key performance indicators and assess the impact of product features.

Communicate complex technical concepts effectively to both technical and non-technical audiences, including product managers, stakeholders and leadership.

Knowledge/Skills/Abilities:

Proven experience applying a strong scientific foundation to contextualize and interpret multimodal data.

Applied research and development experience with data preparation & analysis, data cleaning (including signal processing), knowledge extraction & interpretation, coding, and deployment (e.g., Python).

Proven experience developing, designing, constructing, and maintaining data structures, models, physical databases, and algorithms rather than relying on out-of-the-box solutions.

Experience leading predictive modeling and programming, especially with unstructured data; provide project examples to demonstrate ability

Applied research experience using machine learning/artificial intelligence techniques to accomplish various types of detection/classification and prediction.

An understanding of underlying theories and experience developing solutions using multiple advanced modeling approaches, such as the following: machine learning, reinforcement learning, algorithm design, data analysis, image analysis, feature extraction, and pattern recognition.

Ability to succinctly translate technical findings to non-technical people; experience writing technical reports and grant proposals.

Comfort in ambiguity to lead research related to a specific domain and provide actionable recommendations.

Demonstrate strong visualization skills (i.e., ability to tell a story with data; turn data into insight)

Additional Skills & Qualifications

MS&T industry

AR / VR / XR

Experience Level

Expert Level