L.E.K. Consulting is looking for a Data Scientist to help solve complex business problems for their clients by leveraging data and analytics. The role involves executing advanced analytics, building innovative tools, and driving technical roadmaps to provide analytically driven recommendations.
Requirements
- 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
- 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 both structured and unstructured datasets; comfort with best data acquisition and warehousing practices
Responsibilities
- Support 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
- 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 modelling, NLP, GenAI etc.), and visualizations
- Drive the development of state-of-the-art analytical apps, leveraging up-to-date machine learning algorithms to solve complex problems
- Provide technical expertise and thought leadership on developing analytical tools, services lines, and proprietary data assets, and contribute to building these areas directly when applicable
- Stay up to date on best-in-class software, tools, and techniques to ensure that we are able to provide clients with best-in-class solutions
- Help drive the technical roadmap to ensure we are operating a best-in-class Data & Analytics function
Other
- Support clients in strategically leveraging technical models, guiding them through the interpretation of results and the integration of actionable insights into their business workflows.
- Collaborate with a variety of stakeholders to continuously innovate on the apps, service lines and proprietary data assets we can offer
- When relevant, support Managing Directors in developing and delivering client proposals where advanced data and analytics are critical to the scope of work
- Provide input into training / upskilling the D&A team provides to Managing Directors to ensure they are aware of all of our most current capabilities
- Proficient Excel, PowerPoint presentation and excellent communication skills, both written and oral; ability to explain complex algorithms to business stakeholders
