Chief Data Science Strategist
hace 3 días
We are seeking a highly skilled Chief Data Science Strategist to join our team at Publicis Sapient. As a key member of our data science team, you will play a crucial role in driving digital transformation strategies for our clients globally.
This is an excellent opportunity to leverage your expertise in machine learning, artificial intelligence, and data analytics to drive business growth and innovation. You will collaborate with cross-functional teams, including digital directors, client teams, and practice capabilities to ensure that our company leads in digital thinking, execution, and value realization through data-driven solutions.
Your Impact:- You will contribute to the development of cutting-edge AI and machine learning initiatives, building data science models, and performing research to solve complex marketing and business challenges.
- You will work closely with internal and external stakeholders to establish objectives, deliverables, and timelines for various projects.
- You will design and implement scalable data pipelines for real-time modeling frameworks, apply quantitative techniques to build predictive models, and uncover patterns in data.
- You will document and visualize your work for both technical and non-technical audiences, ensuring quality and timely delivery of engagements with minimal supervision.
We offer a competitive salary of $180,000 - $220,000 per annum, based on experience and qualifications. In addition, you will have access to a comprehensive benefits package, including health insurance, retirement plans, and paid time off.
We are committed to creating a diverse and inclusive work environment, where everyone has the opportunity to thrive. Our company culture values collaboration, innovation, and continuous learning, providing a dynamic and challenging work environment.
Requirements:- You should hold a graduate degree (Master's or PhD preferred) in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Applied Mathematics, or related fields.
- You should have strong foundation in statistical concepts and Machine Learning techniques, including time series forecasting, regression techniques, logistic regression, ARIMA, clustering, classification, decision trees, among others.
- You should be proficient in advanced techniques like RNN, LSTM, GBM, SVM, Random Forest, and State Space Modelling.
- You should have hands-on experience with Python, SQL, Machine Learning, ML-Flow, and Azure Cloud.
- You should have experience with solution design, data visualization, data pipelines, model comparison, and evaluation.
- You should be able to translate complex analytics output into actionable business recommendations and insights.
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