We are excited to expand our business in the advanced advertising space with our Consumer Canvas dataset and MRI-Simmons truth set. We are dedicated to transforming the way marketers can activate and measure with more transparency and confidence. The Product Technology leader will be responsible for driving the technical direction and engineering execution of our digital growth products. This role requires a deep understanding of big data product management, big data processing, analytics & measurement, audiences, and adtech. The ideal candidate will have a proven track record of leading data product teams, data products involving data science, and developing scalable solutions, and delivering impactful results. This role would report to the SVP of Product Strategy.Key Responsibilities This role will be responsible for digital data products and technology necessary to shape our data and tech landscape in support of business goals in areas of Audiences, Activation, Measurement, Data Processing and Data & Insight Enablement.Lead Product Development: Guide and manage the team in the development of product features, ensuring they meet high-quality standards and align with the product roadmap. - Make technical decisions that balance user needs, product goals, business objectives. - Ensure the product is scalable, maintainable, and aligned with long-term strategy. - Foster a culture of innovation, encouraging the team to explore new technologies, tools, and approaches that can enhance the product and development process. - Promote a culture of experimentation, iteration, and learning within the team.Technical Proficiency: Deep understanding of data product technologies, including databases, data analytics, machine learning, and cloud computing. This helps in making informed decisions and guiding the team effectively. Make strategic decisions regarding the architecture, tools, and frameworks used in the product development process.1. Data Technologies: This includes understanding various types of databases (SQL, NoSQL), data warehousing solutions, data lakes, and big data technologies like Hadoop and Spark. Familiarity with data integration tools and ETL (Extract, Transform, Load) / ELT, are important2. Data Analytics and Visualization: Proficiency in data analytics tools (e.g., Python, R, SAS) and visualization platforms. This helps in interpreting data, generating insights, and presenting findings in a comprehensible manner.3. Machine Learning and AI: Knowledge of machine learning algorithms, frameworks (e.g., TensorFlow, PyTorch), and AI techniques is valuable. This enables the leader to guide the development of predictive models and intelligent systems.4. Cloud Computing: Understanding cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services is critical. This includes knowledge of cloud storage, data processing, and cloud-native architectures.5. Data Governance and Security: Awareness of data governance principles, data privacy laws and security best practices. This ensures that data is managed responsibly and securely.6. Continuous Learning: The tech landscape is always evolving, so a good leader stays updated with the latest trends, tools, and technologies. This might involve attending conferences, participating in online courses, or engaging with professional communities.Communication Skills: Strong communication and interpersonal skills are vital for explaining complex technical concepts to non-technical stakeholders and for building relationships within the team.Team Management: A commitment to team building and mentoring is important. This includes fostering a collaborative environment and supporting the professional development of team membersProblem-Solving Skills: Effective leaders need to be adept at identifying and solving problems quickly and efficiently. This involves critical thinking and the ability to navigate challengesAdaptability: The data enablement industry is constantly evolving, so being adaptable and open to change is essential. This includes being able to pivot strategies and embrace new technologies and methodologies as needed to support products.Stakeholder Collaboration: Collaborate with cross-functional teams, including product management, to drive cohesive strategies and achieve business objectives.Business Acumen: Understanding the business side of technology, including market needs, customer expectations, and financial implications. This helps in making decisions that are not only technically sound but also commercially viable.Ethical Judgment: Ensuring data privacy and security, and making ethical decisions that align with the company's values and societal expectations.Key Activities: 1. Strategic Planning: Developing a technology roadmap outlining how we plan to develop and deliver against company's goals and product initiatives.2. Project Oversight: Ensuring successful delivery of products by overseeing timelines, budgets, and resource allocation3. Risk Management: Identifying and mitigating technical risks to ensure the stability and security of systems and products4. Performance Monitoring: Tracking and analyzing key performance indicators (KPIs) to measure the success of initiatives5. Budget Proposals: Financial plans that outline the costs associated with development initiatives and justify the investment6. Technical Architecture Diagrams: Visual representations of the system architecture, showing how different components interact7. Innovation Proposals: Documents proposing new technologies or processes that could benefit the organization
