Senior Manager Applied Science

• Lead, mentor, and manage a team of applied scientists, including senior scientists and team leads.

• Lead, mentor, and manage a team of applied scientists, including senior scientists and team leads.
• Build and scale a high-performing team of 5-8 scientists; provide regular mentoring and establish clear career development paths.
• Set and promote best practices for research, development, code quality, and technical excellence

• Collaborate with product and customer success teams to prioritize customer needs and align development timelines accordingly.

• Collaborate with product and customer success teams to prioritize customer needs and align development timelines accordingly.
• Integrate customer feedback into development cycles, adapting priorities as business needs evolve.
• Act as the technical point of contact for customer engagements, setting clear expectations for deliverables and timelines.
• Ensure high-quality, on-time delivery of customer-facing AI/ML products that meet or exceed expectations.

• Lead the execution of the R&D and product roadmap, aligning ML initiatives with business goals and customer priorities.

• Lead the execution of the R&D and product roadmap, aligning ML initiatives with business goals and customer priorities.
• Drive product strategy in collaboration with product management, business development, and operations.
• Provide architectural and technical leadership on key projects, ensuring robustness, scalability, and flexibility.

• Foster a high-performing team through agile workflows, continuous improvement, and strong delivery processes.

• Foster a high-performing team through agile workflows, continuous improvement, and strong delivery processes.
• Architect and implement scalable AI/ML solutions aligned with ASD's long-term vision, using cloud-native technologies and microservices.
• Oversee the full ML lifecycle-including data collection, model training, validation, deployment, and monitoring-ensuring effective team collaboration and resource management.
• Promote advanced techniques such as model compression, quantization, and distributed training.
• Champion industry best practices in development to ensure code quality, performance, and scalability.
• Stay current with advancements in ML and lead team engagement in the broader scientific community.
• Collaborate with design, product, and engineering teams to deliver high-performance solutions in a fast-evolving environment.

• Bachelor’s, Master’s, or Ph.D. in Data Science, Mathematics, Operations Research, Applied Mathematics, Computational Science, or a related field.

• Bachelor’s, Master’s, or Ph.D. in Data Science, Mathematics, Operations Research, Applied Mathematics, Computational Science, or a related field.
• Strong foundation in probability, statistics, and scientific problem-solving.
• 12+ years of hands-on experience in analytics, data science, and deep learning in business-critical environments.
• 3+ years of experience managing teams of 5 or more, preferably in applied science or cross-functional settings..
• Proven track record of delivering high-impact, data-driven solutions to complex business problems.
• Proficient in machine learning, deep learning, and explainable AI techniques, with the ability to communicate technical concepts to non-technical stakeholders.
• Experience developing and deploying state-of-the-art ML models tailored to specific business needs.
• Strong programming skills in Python and SQL; experience with feature engineering and deep learning pipelines.
• Familiarity with deep learning frameworks such as TensorFlow, Keras, and PyTorch.
• Experience with computer vision (e.g., OpenCV) and natural language processing (e.g., spaCy).
• Skilled in the Design of Experiments for scientific testing and optimization.
• Proficient in Git for version control and collaboration.
• Working knowledge of cloud platforms such as AWS, GCP, and Azure.
• Strong analytical thinking and structured problem-solving abilities.
• Excellent communication and collaboration skills in cross-functional teams.

• Demonstrated leadership experience in mentoring junior engineers and managing cross-functional projects.
• Proven innovation track record—solutions that delivered significant business impact or led to patents.
• Self-motivated, proactive problem-solver with strong project ownership.
• Domain knowledge or experience in recommendation systems, NLP, or computer vision.
• Strong collaboration skills across multiple teams, with an ability to manage conflict and align priorities.