Head of AI & Data Science

HRTx Inc.; Metro Manila; Hybrid; PHP 2,000,000 - 3,000,000; Full time

Job summary

HRTx Inc. is seeking a seasoned Analytics Leader to drive end-to-end AI and data projects for clients. You will define problems, source data, build models, validate, deploy and monitor solutions while guiding a team of AI/ML experts. You’ll translate business goals into analytics strategies and present outcomes to senior stakeholders.

You will architect scalable analytics using Python and cloud technologies, contribute to business development, and mentor junior analysts to grow the practice.

Qualifications

• 12+ years of experience in data science, analytics, or AI modelling.
• Proficiency in Python, R, SQL and data analysis tools.
• Expertise in analytics techniques: optimization, ML, NLP, CV.
• Strong end-to-end project leadership across AI/DS lifecycle.

Responsibilities

• Lead and manage end-to-end AI and data projects for clients.
• Translate business needs into analytics problems and solutions.
• Lead a team of AI/ML experts to deliver high-quality solutions.
• Provide thought leadership on best practices and methodologies.
• Architect scalable analytics using Python and cloud/big data tech.
• Engage in business development and client presentations to seniors.
• Identify opportunities and generate proposals for potential clients.
• Mentor and coach junior analysts and developers on the team.

Skills

Data science leadership

AI/ML expertise

Analytics problem solving

Client engagement

Team leadership

Problem definition

Tools

Python

R

SQL

Pandas

Numpy

Cloud

Job description

Responsible for leading and delivering analytics solutions for our clients and associate functions such as, integrated business planning, produce lifecycle management, procurement transformation, smart manufacturing, digital logistics & fulfilment, and enterprise asset management. The candidate will also be involved in designing and developing analytics models using next generation technologies and Python.

The candidate will also be responsible in running and growing the Organization's Analytics Data Science Practice.

Role Description:

• Lead and manage end to end AI and Data focused projects for clients, including problem definition, data acquisition, model development, validation, deployment and monitoring.
• Work closely with clients and stakeholders to understand their business needs and objectives, and translate them into analytics problems and solutions.
• Lead a team of AI/ML experts to deliver high-quality solutions for clients.
• Provide thought leadership and guidance on best practices and methodologies.
• Architect and implement scalable and robust analytics solutions using Python and next generation technologies such as cloud, big data, AI/ML, etc.
• Get involved in business development, client engagement, proposal writing and presentation of the solutions to senior stakeholders and clients.
• Identify new opportunities and generate proposals for potential clients
• Mentor and coach junior analysts and developers on the team

Key Skills:

• At least 12 years of experience in data science, analytics, or artificial intelligence related modelling in the industry
• Proficiency in Python, R, SQL, and other data analysis tools and platforms
• Strong knowledge of analytical modelling required for fields such as logistics & distribution, inventory management, stock policy, optimization, catalogue health etc.
• Strong expertise in the application of analytical and AI techniques, such as optimization, simulation, machine learning, deep learning, natural language processing, computer vision, etc.
• High expertise in Python and next generation technologies such as cloud, big data, AI/ML, etc.
• Strong knowledge of Pandas and Numpy libraries.
• Excellent mathematical, statistical, and analytical skills.
• Understanding of end-to-end product development lifecycle in different environments such as dev, QA, and production.
• Git version control and Agile development experience.
• Experience in architecting and working on end-to-end analytics project lifecycle, including data acquisition, model development, validation, deployment and monitoring
• Ability to manage clients and stakeholders effectively and build strong relationships
• Ability to translate business problem into analytics problem and vice versa
• Excellent presentation and consulting skills