**Job Description** The role of the Senior Associate is to collaborate with clients undergoing data-driven transformation across the globe. As a key member of the Data Science team, the successful candidate will accelerate and drive the DDT strategy for clients, working in partnership with Digital directors, client teams, and practice capability. **Key Responsibilities:** - Solve complex marketing and business challenges by accessing, integrating, manipulating, mining, and modeling a variety of data sources. - Reframe client business questions into data science deliverables. Contribute to data science roadmap creation. Collaborate with internal and external stakeholders to establish objectives, deliverables, and timelines. - Perform exploratory data analysis, data cleansing, and imputation, feature generation in preparation for the modeling process. - Apply various quantitative techniques to build predictive models and uncover patterns in data. - Build scalable data pipelines and models for real-time modeling frameworks. - Document and visualize your work and outputs for technical and non-technical audiences. - Contribute to the Data Science capability through presenting work, mentoring talent, helping form best practices, and points of view on various AI-related topics. **Requirements:** - Proficiency in several time series techniques: ARIMA, ARIMAX, exponential smoothing, GARCH, regression, moving average, neural networks, LSTM. Strong skills in classification methods: logistic regression, decision trees, random forests, SVM, neural networks, KNN, Naive Bayes. - Advanced proficiency in Python and related technologies. - Graduate degree or equivalent in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, Applied Statistics, Physics, Engineering, or a related field. - Broad awareness of data science concepts including linear regression, logistic regression, correlation variance, standard deviation, dimensionality reduction, unsupervised learning, parameter tuning, cross-validation, bootstrapping, forecasting, and imputation. - Experience with Python, R, TensorFlow, Cortana, Azure, Watson, SPSS, and SAS. - Hands-on experience with data exploration, model comparison, model evaluation, insights/interference, and data interpretation/insight analysis. Demonstrable delivery experience using a wide variety of machine-learning techniques including classifiers, regression, clustering, decision trees, neural networks, NLP, and ensemble techniques. - Experience with customer segmentation, behavior analysis, developing recommender systems, fraud analytics, personalization systems, and forecasting. - Ability to work with data engineers to design and develop data-intensive solutions. - Broad understanding of the digital landscape and Martech principles. Experience with solution design and development, quality assurance and testing, data visualization, and prototyping. - Ability to integrate multiple methods to accomplish specific objectives/projects and apply techniques and learnings from past projects to new projects. - Excellent written and verbal communication skills and the ability to work closely with senior stakeholders.