Product Manager ( Research )

Talener; New York (NY); On-site; USD 140,000 - 185,000; Full time

Job summary

Talener is seeking a Product Manager (Research) in New York, NY, offering a hybrid work setup. The role focuses on building a proprietary discovery engine that converts real-time data streams into structured assets, predictive indicators, and machine-readable context layers.

You will drive product discovery across data platforms and ML-enabled systems, collaborating with data scientists and engineers to shape development roadmaps.

Qualifications

• 5 years of professional experience driving technical product discovery across data platforms, machine learning products, automated retrieval systems, or complex analytics platforms.
• Demonstrated ability to turn ambiguous data challenges into structured research plans and actionable development roadmaps.
• Fluency interrogating complex datasets using SQL, Python, and Jupyter environments.

Responsibilities

• Lead technical product discovery across data platforms and analytics initiatives.
• Collaborate with cross-functional teams to define roadmaps and deliverables.
• Translate complex data insights into practical product strategies for stakeholders.

Skills

Product discovery

Data platforms

Machine learning products

Automated retrieval systems

Analytics platforms

Tools

SQL

Python

Jupyter

Job description

Product Manager (Research)

Location: New York, NY (Hybrid)

Compensation: $140,000 – $185,000 + Comprehensive Benefits

About the Opportunity

We are recruiting for a dedicated innovation team within a global technology and data solutions provider. The team is building a proprietary discovery engine that transforms high-volume streams of real-time market and geopolitical activity into structured data assets, predictive indicators, and machine-readable context layers.

Requirements & Qualifications

• 5 years of professional experience driving technical product discovery across data platforms, machine learning products, automated retrieval systems, or complex analytics platforms.
• Demonstrated ability to take ambiguous data challenges and turn them into structured research plans and actionable development roadmaps.
• Practical, hands-on fluency interrogating complex datasets using tools like SQL, Python, and Jupyter environments.
• Operational understanding of modern data technologies, including retrieval-augmented generation, vector embeddings, structured schemas, ontologies, and model performance metrics.
• Exceptional communication skills with a track record of distilling technical insights for cross-functional teams, executive leadership, and commercial clients.
• Strong commercial instinct to balance experimental curiosity with scalable business outcomes.