Descripción del empleo The purpose of the Senior Associate is to work with clients undergoing a data-driven transformation (DDT) across the globe.
The Senior Associate will accelerate and drive the DDT strategy for clients, working in partnership with Digital directors, client teams, and practice capability.
Furthermore, the role will be a key contributor in ensuring the agency is an industry leader in digital thinking, execution, and value realization for clients through data-driven solutions.
Your Impact: You will function as part of a world class Data Science team to support various AI and machine learning initiatives 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 Use distributed computing systems to ingest, access and integrate various big data sources Perform exploratory data analysis, data cleansing and imputation, feature generation in preparation to the modelling process Apply various quantitative techniques to build predictive models and uncover patterns in data Build scalable data pipelines and models for real-time modelling 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 point of views on various AI-related topics Requisitos 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