Data Scientist V

In this role, you will be involved in specific engagements involving the building of new, bespoke advanced analytical solutions for clients. Leveraging your advanced data analysis skills, you will create innovative approaches to answer our clients' most relevant questions, prepare complex data analyses and models to help solve client problems, and deliver significant measurable impact. As an analytics translator, you will communicate complex data-related requirements between business and IT stakeholders. You should have a strong understanding of the design and development process of data analytics tools and experience working with data engineers. Key Responsibilities: - Minimum of 12 years experience with advanced knowledge of statistical and data mining techniques such as regression, decision trees, clustering, neural networks, etc. - Experience in working with large datasets and relational databases, with a preference for knowledge of SQL. - Knowledge of additional programming languages is a plus, such as Python, C, and Java. - Demonstrated distinctive communication skills and the ability to convey analytical and technical content in an easy-to-understand manner. - Intellectual curiosity, excellent problem-solving skills, and quantitative skills, including the ability to disaggregate issues, identify root causes, and recommend solutions. - Proven leadership skills with the ability to inspire others, build strong relationships, and achieve results. - Strong people skills, team-orientation, and a professional attitude. Core ML Skills: - Experience with supervised and unsupervised learning algorithms. - Expertise in time series analysis for forecasting and anomaly detection. - Knowledge of clustering and classification techniques like K-Means, DBSCAN, Random Forest, XGBoost. - Experience with anomaly detection frameworks such as Isolation Forest, Autoencoders, etc. - Familiarity with causal inference and root cause analysis techniques. - Experience with cost forecasting models like ARIMA, Prophet, LSTM. - Proficiency in Python and/or R, along with libraries like pandas, scikit-learn, PyTorch, TensorFlow. Nice To Have: - Experience with hybrid cloud environments. - Experience with agent-based architectures like CrewAI, LangGraph, AutoGen, MetaGPT. - Experience with Graph ML including Graph Convolutional Networks, Node2Vec, DeepWalk. Qualifications Required: - Bachelor's degree in a quantitative field such as Computer Science, Engineering, Statistics, Mathematics, or a related field is required. - An advanced degree is considered a strong plus in this role. In this role, you will be involved in specific engagements involving the building of new, bespoke advanced analytical solutions for clients. Leveraging your advanced data analysis skills, you will create innovative approaches to answer our clients' most relevant questions, prepare complex data analyses and models to help solve client problems, and deliver significant measurable impact. As an analytics translator, you will communicate complex data-related requirements between business and IT stakeholders. You should have a strong understanding of the design and development process of data analytics tools and experience working with data engineers. Key Responsibilities: - Minimum of 12 years experience with advanced knowledge of statistical and data mining techniques such as regression, decision trees, clustering, neural networks, etc. - Experience in working with large datasets and relational databases, with a preference for knowledge of SQL. - Knowledge of additional programming languages is a plus, such as Python, C, and Java. - Demonstrated distinctive communication skills and the ability to convey analytical and technical content in an easy-to-understand manner. - Intellectual curiosity, excellent problem-solving skills, and quantitative skills, including the ability to disaggregate issues, identify root causes, and recommend solutions. - Proven leadership skills with the ability to inspire others, build strong relationships, and achieve results. - Strong people skills, team-orientation, and a professional attitude. Core ML Skills: - Experience with supervised and unsupervised learning algorithms. - Expertise in time series analysis for forecasting and anomaly detection. - Knowledge of clustering and classification techniques like K-Means, DBSCAN, Random Forest, XGBoost. - Experience with anomaly detection frameworks such as Isolation Forest, Autoencoders, etc. - Familiarity with causal inference and root cause analysis techniques. - Experience with cost forecasting models like ARIMA, Prophet, LSTM. - Proficiency in Python and/or R, along with libraries like pandas, scikit-learn, PyTorch, TensorFlow. Nice To Have: - Experience with hybrid cloud environments. - Experience with agent-based architectures like CrewAI, LangGraph, AutoGen, MetaGPT. - Experience with Graph ML including Graph Convolutional Networks, Node2Vec, DeepWalk. Qualifications Req