Head of Modelling & Data Science

As an Advanced Analytics Senior Manager at our company, you will play a crucial role in setting the strategic direction for the team, taking ownership of the overall Insights and analysis discipline in the market, and ensuring an integrated response to people-based marketing objectives. Your responsibilities will include: - Developing, implementing, and maintaining advanced analytical models using machine learning algorithms and GenAI applications. - Utilizing various advanced analytics techniques to uncover trends, patterns, and insights from large and complex datasets. - Collaborating with cross-functional teams to identify business needs and deliver data-driven solutions. - Creating visually compelling dashboards and reports to present findings to stakeholders. - Continuously evaluating and improving existing analytics methodologies and models to enhance accuracy and performance. - Staying abreast of industry trends and advancements in analytics and machine learning to drive innovation within the team. - Mentoring junior team members and contributing to knowledge sharing within the organization. Basic qualifications required for this role include: - A Bachelors or Masters degree in Data Science, Business Analytics, Mathematics, Statistics, or a related field. - 10+ 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 for the role include proficiency in various advanced analytics techniques such as: - 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. Additionally, extensive knowledge of machine learning techniques is required, 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 is a plus. Proficiency in data visualization tools such as Tableau or Power BI, strong skills in data management, structuring, and harmonization to support analytical needs are also desired for this role.,