Lead Analyst, Analytics

dentsu

2d•Hybrid

About The Position

The purpose of this role is data analysis/guided deliverable development in support of assessment/strategic deliverables. We are seeking an experienced Lead Analyst, Analytics professional to join our dynamic team. This role will involve hands-on use of machine learning algorithms and Generative AI to drive data-driven decision-making within the retail/CPG domain. The ideal candidate will possess a strong quantitative background, and the ability to translate business problems into scalable analytical solutions. This individual will work closely with cross-functional and client teams. FOR ANY APPLICANT TO BE CONSIDERED, THEY MUST LIVE IN THE EASTERN TIME ZONE.

Requirements

Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, Business Analytics, or a related field.
4–6 years of experience in advanced analytics, data science, machine learning, or a related field.
Effective verbal and written communication skills with client-facing experience.
Proficiency in SQL (Google BigQuery preferred) and Python.
Experience with data visualization tools such as Tableau.
Familiarity with Retail/CPG/Tech industry and experience working with product, transaction, and customer-level data.
Strong data structuring, and analytical problem-solving skills with an inquisitive mindset.
Self-driven, collaborative, and adaptable in a fast-paced environment.
Must live in the Eastern Time Zone.

Responsibilities

Develop, implement, and maintain advanced analytical models using machine learning algorithms and statistical techniques.
Apply descriptive analytics to uncover trends, patterns, and insights from large and complex datasets, using Tableau dashboards and reports where necessary.
Perform customer, product, and transaction-level analysis within retail/CPG datasets.
Assist in the design and implementation of LLM-based embedding-powered solutions like summarization and classification.
Develop and support simulation applications where required.
Work directly with senior client stakeholders, collaborate with cross-functional teams, and contribute end-to-end on solution development.
Write efficient SQL queries (Google BigQuery preferred) and build data transformation workflows in Python.
Ensure data quality, harmonization, and consistency across analytical projects.
Continuously evaluate and improve existing analytics methodologies and models to enhance accuracy and performance.
Stay updated on industry trends in machine learning and AI and contribute to innovation within the team.
Mentor junior team members and contribute to knowledge sharing initiatives.