Publicis Sapient is a digital transformation partner helping established organizations get to their future, digitally-enabled state, both in the way they work and the way they serve their customers. We help unlock value through a start-up mindset and modern methods, fusing strategy, consulting and customer experience with agile engineering and problem-solving creativity. United by our core values and our purpose of helping people thrive in the brave pursuit of next, our 20,000+ people in 53 offices around the world combine experience across technology, data sciences, consulting and customer obsession to accelerate our clients' businesses through designing the products and services their customers truly value. Job Description The Senior/Manager Data Science will support clients undergoing a data-driven transformation (DDT) globally by accelerating and driving the DDT strategy. This role will collaborate with digital directors, client teams, and practice capabilities to ensure that the company leads in digital thinking, execution, and value realization through data-driven solutions. The Senior Associate will play a crucial role in contributing to the company's industry leadership in AI and machine learning, solving complex marketing and business challenges, and pioneering advanced analytics in areas like healthcare. Your Impact: Function as part of a world-class Data Science team, supporting various AI and machine learning initiatives, building data science models and performing cutting-edge research. Solve complex business challenges by accessing, integrating, manipulating, mining, and modeling a variety of data sources. Research and develop new POCs for business applications. Reframe client business questions into data science deliverables and contribute to creating data science roadmaps. 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, feature generation, and model preparation. Apply quantitative techniques to build predictive models, uncover patterns in data, and build scalable data pipelines for real-time modeling frameworks. Document and visualize your work for both technical and non-technical audiences. Mentor talent, help form best practices, and contribute to data science capability through presentations and thought leadership on AI-related topics. Manage the continuous improvement of data science initiatives, staying updated with state-of-the-art research in the field. Research new opportunities, build proof-of-concept (POC) models, and work closely with leadership to devise strategies for implementing advanced analytics. Work from analytical design to implementation, ensuring quality and timely delivery of engagements with minimal supervision. Collaborate with business teams to operationalize analytics solutions, especially in operational analytics and US healthcare domains, including epidemiology. Qualifications Your Skills & Experience: 5-12 years of experience in the analytics industry. Graduate degree (Master's or PhD preferred) in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Mathematics, or related fields. Strong foundation in statistical concepts and Machine Learning techniques: including time series forecasting, regression techniques, logistic regression, ARIMA, clustering, classification, decision trees, among others. Proficiency in advanced techniques like RNN, LSTM, GBM, SVM, Random Forest, and State Space Modelling. Hands-on experience with Python, SQL, ML-Flow, and Azure Cloud. Experience with solution design, data visualization, data pipelines, model comparison, and evaluation. Ability to translate complex analytics output into actionable business recommendations and insights. Prior experience in research or publications in the data science field is highly preferred. Great interpersonal and communication skills, with the ability to work closely with senior stakeholders in a fast-paced environment. Set Yourself Apart With: Working experience with advanced techniques such as GBM, NLP, and NoSQL databases. Experience with tools like Hive, Spark, and Teradata. Experience with mainstream machine learning frameworks such as TensorFlow, PyTorch, ConvNet. Understanding of the US healthcare domain, particularly in operational analytics and epidemiology. #J-18808-Ljbffr