Logo of Huzzle

Home

Matches

Explore

Manage

Data Scientist

image

L.E.K. Consulting

Jul 17

  • Job
    Full-time
    Mid & Senior Level
  • Data
  • $80K - $145K
  • Los Angeles, +4

AI generated summary

  • You need a quantitative degree, 2-4 years in data science, expertise in Python, machine learning, cloud services, MLOps, and strong communication skills. Consulting experience is a plus.
  • You will lead data science projects, deploy machine learning models, solve analytical challenges, develop analytical apps, support client proposals, mentor team members, and stay updated on industry best practices.

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 both 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 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; and assertive, intellectually curious and continuously driving towards excellence.

Responsibilities

  • Client engagements:
  • 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 modelling, NLP, GenAI etc.), and visualizations
  • Help drive the technical roadmap needed to support client engagements
  • Analytical apps, service lines, and proprietary data assets:
  • Drive the development of state-of-the-art analytical apps, leveraging up-to-date in machine learning algorithms to solve complex problems
  • Collaborate with a variety of stakeholders to continuously innovate on the apps, service lines and proprietary data assets we can offer
  • 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
  • Uphold best-in-class standards in app development, data integrity, and ensuring solutions are both scalable and maintainable
  • Client / business development:
  • 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
  • Capability development:
  • 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
  • Support commercialization and upskilling of staff on relevant software, tools and techniques
  • Help drive the technical roadmap to ensure we are operating a best-in-class Data & Analytics function
  • Mentor team members, contribute to technical capabilities of the team

FAQs

What are the key responsibilities of a Data Scientist at L.E.K. Consulting?

The key responsibilities include leading end-to-end data science projects, supporting clients in leveraging technical models, solving complex analytical challenges, developing analytical apps and proprietary data assets, assisting in client business development, and contributing to capability development through mentoring and technical expertise.

What qualifications and experience are required for this Data Scientist position?

A degree in a quantitative or business discipline is preferred, along with a minimum of 2 years of experience in applied data science for a Data Scientist role (or 4 years for a Senior Data Scientist). Candidates should have strong knowledge of machine learning and statistical modeling, proficiency in tools like Python, SQL, and cloud platforms, and experience with MLOps practices.

What tools and technologies should candidates be familiar with?

Candidates should be fluent in Python and its data science and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch), SQL, and have experience with Spark. Familiarity with Alteryx and Tableau is preferred, along with expertise in deploying machine learning models in cloud environments such as AWS, Azure, or GCP.

Is experience in consulting firms considered advantageous for this role?

Yes, experience with commercial business analytics and at a consulting firm or agency is considered a plus for this position.

What type of analytical challenges will the Data Scientist be expected to solve?

The Data Scientist will tackle a wide variety of complex analytical challenges including data aggregation, data cleaning, commercial data science techniques (e.g., geospatial analysis, machine learning, predictive modeling, NLP), and creating visualizations.

How important is communication in this role?

Communication is extremely important in this role, as Data Scientists must effectively explain complex algorithms and insights to business stakeholders, and collaborate with various team members and clients.

What kind of training and development opportunities does L.E.K. Consulting offer for this position?

L.E.K. Consulting offers state-of-the-art training in various domains, opportunities for skill development, and mentorship within the team to help drive capability development and innovation.

How does a Data Scientist contribute to client engagements?

A Data Scientist leads data science projects from conceptualization to deployment, supports clients in interpreting results, helps integrate actionable insights into their business workflows, and assists in optimizing technical models for performance and scalability.

What is the role of the Data Scientist in business development?

The Data Scientist supports Managing Directors in developing and delivering client proposals where advanced data and analytics are critical, and contributes to training efforts to enhance the capabilities of the team.

What is expected from the Data Scientist in terms of technical leadership?

The Data Scientist is expected to provide technical expertise and thought leadership on developing analytical tools, uphold best-in-class standards, and help drive the technical roadmap for the Data & Analytics function.

L.E.K. Consulting

See the world while helping to shape it

Consulting
Industry
1001-5000
Employees
1983
Founded Year

Mission & Purpose

L.E.K. Consulting is a global management consulting firm that specialises in providing strategic advice and solutions to clients across various industries. Their team of experienced consultants offers expertise in areas such as business strategy, mergers and acquisitions, market research, operations, and more. L.E.K. Consulting's ultimate mission is to help clients achieve exceptional results and create long-term value. They work closely with organisations to identify opportunities, solve complex problems, and drive sustainable growth. By combining rigorous analysis, industry insights, and innovative thinking, L.E.K. Consulting enables clients to make informed decisions and stay ahead in today's competitive business landscape.