Product Lead

Summary:

The Product Lead at Ycotek will be responsible for defining and driving the strategy, roadmap, and execution of our products. You will collaborate with cross-functional teams to develop and deliver impactful products that meet customer needs and align with business objectives.

Key Responsibilities    

• Define the product vision, roadmap, and goals, ensuring alignment with business objectives set by stakeholders.

• Lead collaboration across engineering, design, marketing, and sales teams to successfully execute product features.

• Oversee the product lifecycle from concept and design to development, testing, launch, and post-launch optimization, ensuring timely and high-quality delivery.

• Conduct market research and analyze data to prioritize features and continuously improve the product.

• Manage the product backlog, plan sprints, and guide the team through the Agile development process.

• Establish and monitor key performance indicators (KPIs) to assess product success and impact.

• Lead and mentor junior team members, fostering professional development and team growth.

Key Specifications

• Bachelor’s degree in Computer Science, Engineering, or a related field.

• 5+ years of experience in product management.

• Strong knowledge of product development processes, Agile methodologies, and product management tools (e.g., Jira, Trello).

• Ability to make data-driven decisions with a keen focus on performance and product optimization.

• Strong product sense with the ability to identify issues and envision effective solutions.

• Familiarity with technology and software development processes; capable of effective communication with technical teams.

• Ability to manage competing priorities and navigate complex, ambiguous situations in a fast-paced environment.

• Exceptional communication skills with the ability to influence, partner with, and build relationships across all levels of the organization.

• Understanding of machine learning algorithms (e.g., clustering, decision trees, neural networks, LLMs) and their real-world advantages and drawbacks.

• Knowledge of advanced statistical techniques (e.g., regression, distributions, statistical tests) and their practical applications.

Desirable Experience & Skills

• Experience in natural language processing (NLP), computer vision, or other specialized AI fields is a plus. 

• Experience with Python and SQL to manipulate and analyze large datasets.

• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) for deploying AI models.  

• Familiarity with MLOps tools and frameworks for model management and deployment (e.g., MLflow, Kubeflow, Docker). 

• Experience of programming languages like C++, Java and Scripting Language (JavaScript). 

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