About the Role:
We are seeking a highly skilled
Technical Product Owner
with deep expertise in
Data & AI
to lead the development of innovative data-driven products and AI solutions. You will bridge the gap between business stakeholders and engineering teams, ensuring that our data initiatives align with strategic objectives and deliver measurable impact.
Key Responsibilities:
-
Act as the
Product Owner
for Data & AI initiatives, managing the
product backlog
, prioritizing features, and defining user stories.
-
Collaborate closely with
Data Engineers, Data Scientists, and AI teams
to translate business requirements into technical solutions.
-
Drive the
end-to-end lifecycle
of AI/ML and data products, from ideation and requirements gathering to deployment and monitoring.
-
Ensure alignment of data strategies with
business objectives
, including analytics, predictive modeling, and AI use cases.
-
Define
technical product roadmaps
and drive adoption of best practices in data architecture, governance, and AI deployment.
-
Collaborate with
stakeholders
to understand their needs and translate them into actionable features.
-
Measure product performance using relevant KPIs and iterate on features for continuous improvement.
-
Stay abreast of the
latest trends in AI, machine learning, and data technologies
, evaluating opportunities for innovation.
Required Qualifications:
-
Bachelor’s or Master’s degree in
Computer Science, Data Science, AI, Engineering, or related field
.
-
3_4 Proven experience as a
Technical Product Owner
in
data-intensive or AI-focused projects
.
-
Strong understanding of
data engineering, AI/ML models, data pipelines, cloud data platforms (AWS, Azure, GCP)
.
-
Experience with
analytics, AI/ML frameworks (TensorFlow, PyTorch, scikit-learn), and data visualization tools
.
-
Solid knowledge of
agile methodologies
, backlog management, and working with cross-functional teams.
-
Excellent
communication skills
to bridge technical and business conversations.
-
Strong problem-solving skills and the ability to make
data-driven product decisions.