Data Science Expert

hace 2 semanas

Puerto Diablo Barrio, Puerto Rico Jobleads-Us A tiempo completo

About L.E.K. Consulting
L.E.K. Consulting is a global management consulting firm that uses deep industry expertise and rigorous analysis to help business leaders achieve practical results with real impact. We are uncompromising in our approach to helping clients consistently make better decisions, deliver improved business performance and generate greater shareholder returns. The firm advises and supports global companies that are leaders in their industries — including the largest private and public sector organizations, private equity firms and emerging entrepreneurial businesses. Founded more than 35 years ago, L.E.K. employs more than 2,200 professionals across the Americas, Asia-Pacific and Europe. For more information, go to www.lek.com
Overview of the Data & Analytics team
L.E.K.'s Data & Analytics function is focused on creating and deploying best-in-class capabilities to drive business results for our clients. The team is comprised of data scientists, data engineers, technical business analytics consultants, and product managers who work together to solve some of the most challenging business problems our clients have. We drive the full analytics life cycle on client engagements: scoping and understanding business challenges, developing and maintaining robust data assets, creating and running innovative analytical techniques, generating compelling visualizations to communicate the findings/recommendations. We coach, mentor and train colleagues from across the business, on everything from what types of commercial problems analytical techniques can help solve to in-depth technical training for specific types of analysis.
Job Description
We are actively looking for a Data Scientist or Senior Data Scientist to join L.E.K.'s rapidly growing Data & Analytics team. The primary focus of this role is to provide technical expertise: helping to execute on complex analytics across a wide variety of often fast-paced client engagements, helping to build innovative tools and applications that can help solve clients' commercial issues, helping to execute cutting-edge analytical techniques, helping to drive technical roadmaps for the function and firm, and training our colleagues.
Key Responsibilities
• Lead end-to-end data science projects from conceptualization through to deployment, and deploy advanced machine learning models in clients' cloud environments, optimizing for scalability, performance, and reliability to address specific business challenges and objectives.
• Support clients in strategically leveraging technical models, guiding them through the interpretation of results and the integration of actionable insights into their business workflows.
• Solve a wide variety of complex analytical challenges for clients, sometimes dynamically balancing multiple client engagements at one time.
• Analytical needs can include: data aggregation/creation, data cleaning/manipulation, commercial data science (e.g., geospatial, machine learning, predictive modeling, NLP, GenAI etc.), and visualizations.
• Help drive the technical roadmap needed to support client engagements.
Requirements
• Degree in a quantitative and/or business discipline preferred, examples include: Statistics, Computer Science, Data Science, Mathematics, Operations Research, Engineering, Economics.
• A minimum of 2 years of experience in applied data science with a solid foundation in machine learning, statistical modeling, and analysis is required for a Data Scientist.
• A minimum of 4 years of experience in applied data science with a solid foundation in machine learning, statistical modeling, and analysis is required for a Senior Data Scientist.
• Strong knowledge, experience, and fluency in a wide variety of tools including Python with data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch), Spark, SQL; familiarity with Alteryx and Tableau preferred.
• Technical understanding of machine learning algorithms; experience with deriving insights by performing data science techniques including classification models, clustering analysis, time-series modeling, NLP; technical knowledge of optimization is a plus.
• Expertise in developing and deploying machine learning models in cloud environments (AWS, Azure, GCP) with a deep understanding of cloud services, architecture, and scalable solutions (e.g., Sagemaker, Azure ML, Kubernetes, Airflow).
• Demonstrated experience with MLOps practices, including continuous integration and delivery (CI/CD) for ML, model versioning, monitoring, and performance tracking to ensure models are efficiently updated and maintained in production environments.
• Hands-on experience with manipulating and extracting information on a variety of large structured and unstructured datasets; comfort with best data acquisition and warehousing practices.
• Experience with commercial business analytics; experience at a consulting firm/agency is a plus.
• Proficient in Excel, PowerPoint presentation and excellent communication skills, both written and oral; ability to explain complex algorithms to business stakeholders.
• Ability to achieve results through others; experience and proven success record working in matrix, agile and fast-growing environments; assertive, intellectually curious and continuously driving towards excellence.

For more information and to apply

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