Job
Description
Role & responsibilities We are seeking an experienced Advanced Analytics Manager to join our dynamic team. This role focuses on leveraging advanced analytics techniques, including machine learning algorithms, Generative AI (GenAI), and large language models (LLMs), to drive data-driven decision-making within the retail/CPG domain. Key Responsibilities: Develop, implement, and maintain advanced analytical models using machine learning algorithms and GenAI applications Utilize various advanced analytics techniques to uncover trends, patterns, and insights from large and complex datasets. Collaborate with cross-functional teams to identify business needs and deliver data-driven solutions. Create visually compelling dashboards and reports to present findings to stakeholders. Continuously evaluate and improve existing analytics methodologies and models to enhance accuracy and performance. Stay abreast of industry trends and advancements in analytics and machine learning to drive innovation within the team. Mentor junior team members and contribute to knowledge sharing within the organization. Preferred candidate profile Basic Qualifications: Bachelors or Masters degree in Data Science, Business Analytics, Mathematics, Statistics, or a related field. 8+ years of experience in advanced analytics, data science, machine learning, Generative AI or a related field. Strong experience with quantitative modeling, predictive analytics, text analytics, and forecasting methodologies Proficiency in SQL (or Google BigQuery), Python, visualization tools like Tableau/PowerBI Familiarity with the Retail/CPG/Tech industry and experience with product, transaction, and customer-level data. Excellent communication skills, both verbal and written, with the ability to convey complex concepts to non-technical stakeholders. Strong analytical and problem-solving skills, with an inquisitive mindset Desired Skills: Proficient in the following advanced analytics techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression analysis, time series forecasting, classification techniques, market mix modeling Prescriptive Analytics: Optimization, simulation modeling. Text Analytics: Natural Language Processing (NLP), sentiment analysis. Extensive knowledge of machine learning techniques, including: Supervised Learning: Linear regression, logistic regression, decision trees, support vector machines, random forests, gradient boosting machines among others Unsupervised Learning: K-means clustering, hierarchical clustering, principal component analysis (PCA), anomaly detection among others Reinforcement Learning: Q-learning, deep Q-networks, etc. Experience with Generative AI and large language models (LLMs) for text generation, summarization, and conversational agents. Researching, loading and application of the best LLMs (GPT, Gemini, LLAMA, etc.) for various objectives Hyper parameter tuning Prompt Engineering Embedding & Vectorization Fine tuning Proficiency in data visualization tools such as Tableau or Power BI. Strong skills in data management, structuring, and harmonization to support analytical Perks and benefits Good hike on current CTC Insurance Hybrid work mode
