Senior Applied Science Manager

3 weeks ago

Bengaluru, Karnataka, India Diligent Full time

About Us

Diligent is a leading provider of modern governance solutions, empowering over 1 million users and 700,000 board members and leaders with a holistic view of their organization's GRC practices.

As a global company, we foster a collaborative and innovative team culture, empowering our employees to drive impactful decisions and lead with purpose.

Position Overview:

We are seeking a talented and experienced Applied Science Manager to lead and grow a team of applied scientists and machine learning engineers.

This role involves overseeing the development and implementation of platform-level AI capabilities, such as document set comprehension, longitudinal insight extraction, semantic search, and structured retrieval augmented generation, to accelerate AI adoption across Diligent's diverse product suite.

Key Responsibilities:

  • Lead, mentor, and grow a team of applied scientists and machine learning engineers.
  • Foster a collaborative and innovative team culture.
  • Set clear goals and expectations for team members, providing regular feedback and performance reviews.
  • Develop and manage research plans, ensuring timely delivery of high-quality platform-level AI solutions.
  • Collaborate with stakeholders to understand business needs and translate them into technical requirements.
  • Communicate complex technical concepts and project status to non-technical stakeholders.
  • Work closely with cross-functional teams, including applied scientists, machine learning engineers, software engineers, and product managers, to integrate AI-based capabilities into Diligent's products.
  • Oversee the design and development of machine learning approaches for various applications.

Qualifications:

  • 5+ years of hands-on experience in data science, applied science, machine learning, or related discipline.
  • 3+ years of experience leading applied science, data science, or machine learning teams.
  • Experience with Python, NumPy, scikit-learn, Pandas, NLTK, spaCy, PyTorch, or similar.
  • Experience with model deployment and scaling.
  • Foundational knowledge in NLP, machine learning, and statistical modeling.
  • Experience in building ML/AI pipelines and relevant tools such as MLFlow, AWS SageMaker, or similar.

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