Offer summary

Qualifications:

10-12+ years of experience in data science, machine learning, or AI with a proven leadership track record., Strong understanding of system integration principles and the ability to design AI/ML solutions., Experience in industry verticals like Fintech or Healthcare, along with relevant certifications in data science or AI., Proficiency in programming languages such as Python, R, and Java, and familiarity with AI libraries like TensorFlow and PyTorch..

Key responsibilities:

Develop and execute a strategic roadmap for data platform modernization and AI practice.

Engage with clients to design and deliver customized data and AI solutions.

Lead and mentor a team of data and AI specialists, ensuring successful project delivery.

Oversee the design and implementation of data and AI solutions, collaborating with cross-functional teams.

Job description

Title: Director – Data Science & ML Delivery
Location: Remote
Type: Fulltime

Position Overview:

We are seeking an experienced Data and AI Practice Leader; you will be at the forefront of driving innovation and implementing cutting-edge data engineering and artificial intelligence solutions for our clients.
You will lead a team of skilled professionals, collaborating with clients to understand their unique challenges and delivering tailored solutions that leverage data-driven insights to drive business transformation.

Role & Responsibilities:

Strategic Leadership:
Develop and execute a strategic roadmap for the data platform modernization and AI practice, aligning with the firm's overall objectives and market trends.
Identify opportunities for innovation and differentiation, leveraging data and AI to solve complex business problems and create value for Client clients.
Client Engagement:
Engage with clients to understand their business objectives, challenges, and opportunities, and collaborate with them to design and deliver customized data and AI solutions.
Serve as a trusted advisor, providing expertise on industry best practices, emerging technologies, and innovative approaches to leveraging data for competitive advantage.
Team Management:
Lead and mentor a team of data, machine learning, BI and AI specialists, fostering a culture of collaboration, innovation, and excellence.
Provide guidance on project scoping, resource allocation, and technical direction, ensuring successful project delivery and client satisfaction.
Solution Development:
Oversee the design, development, and implementation of data and AI solutions, ensuring alignment with client requirements, industry standards, and best practices.
Collaborate with cross-functional teams to integrate data science and AI/ML capabilities into existing systems and workflows, maximizing impact and value for clients.
Thought Leadership and Innovation:
Stay abreast of industry trends, emerging technologies and best practices in data engineering and AI, and drive innovation through research, experimentation, and knowledge sharing.
Contribute to thought leadership initiatives, such as whitepapers, blogs, and presentations, showcasing the firm's expertise and thought leadership in data-driven solutions.
Pre-sales Support:
Collaborate closely with the sales team to understand the specific requirements and pain points of our clients and develop tailored proposals and solutions.
Conduct client meetings and presentations to articulate the value proposition of our AI/ML/Gen AI services in addressing the unique challenges faced by the key industry sectors.
Work with the sales team to craft responses to RFPs (Request for Proposals) and RFIs (Request for Information) with customized solutions.
Go-to-Market Strategy:
Develop and execute go-to-market strategies specifically targeting the industry verticals, identifying key stakeholders, industry trends, and competitive positioning opportunities.
Collaborate with the marketing team to create targeted collateral, case studies, and thought leadership content highlighting our Data and AI expertise.
Actively participate in industry events, conferences, and forums to promote our AI/ML/Gen AI services and establish thought leadership within the sector.

Qualifications:

Extensive experience (10-12+ years) in data science, machine learning, AI, or related domains, with a proven track record of leading successful projects and teams within a system integration context.
Strong understanding of system integration principles, architectures, and technologies, with the ability to design and implement data science and AI/ML solutions that seamlessly integrate with existing systems and processes.
Experience in at least one of the industry verticals such as Fintech, Life sciences & Healthcare, Manufacturing, or energy & Utilities is MUST, along with relevant certifications in data science, AI, or related fields.
Deep working knowledge of Generative AI and the latest market trends and create a roadmap and vision for our clients.
4-5 years of experience working as a data science practice leader at Big 4 or boutique consulting firms
Excellent communication, leadership, and client-facing skills, with the ability to build trusted relationships, influence stakeholders, and articulate complex technical concepts to diverse audiences.
Strong analytical and problem-solving abilities, with a passion for driving innovation and leveraging data-driven insights to solve business challenges for clients.
Experience in solutions architecture. technical domains such as AI/ML, multimodal ML, model evaluation, MLOps, MLSecOps, ML training, inference, data engineering, data science, fine-tuning
Manage and mentor a team of skilled data scientists, fostering a culture of collaboration, innovation, and continuous learning.
Proficiency in programming languages such as Python, R, and Java, along with experience with data and AI libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Take the lead in designing the AI architecture and selecting technologies from both open-source and commercial offerings.
Knowing the workflow and pipeline architectures of ML and deep learning workloads, including the components and trade-offs across data management, governance, model building, deployment, and production workflows, is crucial.
Experience in advanced analytics tools (Python, R) along with applied mathematics, ML, Deep Learning frameworks (such as TensorFlow), and ML techniques (such as random forest and neural networks).
Experience in Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, Deep Neural Networks,..)
Developing AI and ML models in real-world environments and integrating AI and ML using cloud-native or hybrid technologies into large-scale enterprise applications.

Director – Data Science & ML Delivery

Offer summary

Qualifications:

Key responsibilities:

Job description

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