Senior Manager Applied Science
OtherManager
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Quick Summary
Technical Tools
OtherManager
Requirements
~1 min readResponsibilities
~3 min readLeadership and Team Management
- →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
Customer Engagement & Deliverable Management
- →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.
Product Development & Strategy
- →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.
Scalability & Best Practices
- →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.
Required Qualifications
- →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.
Preferred Qualifications
- →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.
Good-to-have skills
Applied Sciences, Senior Manager, recommendations
Location & Eligibility
Where is the job
Bangalore, India
On-site at the office
About this job
- Posted
- 10 days ago
Listing Details
- Posted
- October 6, 2026
- First seen
- October 6, 2026
- Last seen
- October 15, 2026
Posting Health
- Days active
- 9
- Repost count
- 0
- Trust Level
- 37%
- Scored at
- October 16, 2026
Signal breakdown
freshnesssource trustcontent trustemployer trust
External application
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