Tredence - Manager - Analytics (9-14 yrs)

Company Overview:

Tredence Analytics Solutions is a leading data science and AI engineering company that helps global enterprises solve their most complex business challenges. By bridging the gap between data and actionable insights, the firm enables organizations to make faster, more accurate decisions. Tredence operates across diverse sectors including Retail, CPG, Healthcare, and Telecom, leveraging a deep bench of data scientists and domain experts to deliver scalable, high-impact analytics solutions that drive measurable business value.

Role Overview:

As a Manager, you will lead high-impact analytics engagements, serving as the primary bridge between complex data science capabilities and strategic business objectives. You will work closely with cross-functional teams and senior client stakeholders to translate business problems into advanced analytical models. Your daily focus will involve overseeing the end-to-end delivery of data-driven solutions, ensuring that technical outputs directly influence decision-making processes and improve operational efficiency for our clients.

Total Experience: 9 - 14 years

Key Responsibilities:

- Serve as primary contact to the business for the support and development of AI-enabled and data-driven solutions delivered by internal teams and external vendors

- Manage business and functional requirements for one or more solutions related to Ad Sales, Research, and Digital operations, with a focus on AI/ML use cases (e.g., forecasting, pricing optimization, audience targeting)

- Partner with stakeholders to identify and prioritize opportunities where AI can drive business value

- Translate business needs into detailed functional, data, and analytical requirements, including definition of inputs, outputs, and success criteria

- Facilitate requirement gathering sessions, design workshops, and model validation discussions across business and technical teams

- Work closely with data scientists and engineers to support the design and implementation of AI solutions

- Coordinate testing activities, including user acceptance testing (UAT), ensuring outputs are accurate, interpretable, and aligned with business expectations

- Deliver support to end users on how to effectively use AI-enabled tools and insights in their daily workflows

- Monitor solution performance and support continuous improvement by identifying issues related to data quality, model outputs, or adoption

- Manage relationships with business organizations, global technology teams, and third-party vendors, including reviewing deliverables, timelines, and quality of outputs

- Prioritize enhancement requests alongside other change requests to improve system performance and business outcomes

- Ensure compliance with Software Development Lifecycle documentation and mandated regulatory and audit requirements

- Assist in the design and delivery of training materials and user documentation

- Participate in feasibility studies and evaluation of new AI technologies and vendor solutions

- Work independently under minimal supervision

Basic Qualifications:

- Bachelors degree in Information Systems, Computer Science, Business Administration, Data Analytics, or equivalent degree/work experience

- Minimum of 3-5 years experience with mid to large-scale software development or data-driven projects

- Experience supporting technology solutions within a Media or Digital industry organization

- Strong prioritization and organizational skills

- Strong presentation and communication skills; ability to interface with stakeholders at all levels of the organization

- Strong project management skills

- Excellent problem solving and analytical skills

- Excellent interpersonal skills, including negotiation and conflict resolution

- Ability to manage multiple initiatives simultaneously with minimal supervision

- Proven ability to operate effectively within a fast-paced, matrixed environment

AI & Data Skills:

- Practical understanding of AI/ML concepts and their business application, including predictive modeling, optimization, and recommendation systems

- Ability to translate business problems into structured AI/data use cases, including defining features, inputs/outputs, and success metrics

- Familiarity with the AI/ML lifecycle (data preparation, model training, validation, deployment, monitoring)

- Ability to support business validation of model outputs, ensuring results are interpretable, reliable, and actionable

- Understanding of model performance metrics (e.g., forecast accuracy, precision/recall, lift) and their business implications

- Strong awareness of data quality, data dependencies, and data governance considerations

- Experience working with data scientists and ML engineers, acting as a bridge between technical and business teams

- Working knowledge of data analysis tools (e.g., SQL; exposure to Python or similar tools is a plus)

- Experience with data visualization and BI tools (e.g., Tableau, Power BI) to analyze and communicate insights

- Understanding of experimentation methodologies (e.g., A/B testing, test-and-learn frameworks)

- Awareness of AI governance principles, including explainability, bias, and ethical considerations

- Familiarity with data privacy regulations (e.g., GDPR) and their impact on data and AI solutions

Preferred Qualifications:

- Experience in Ad Sales, Airtime sales, or Research business areas and respective applications

- Experience working within AdTech ecosystems (e.g., OMS, ad servers, programmatic platforms)

- Exposure to AI-enabled products such as forecasting tools, optimization engines, or recommendation systems