Data Science Consultant - Logistics in London

Straive is a global leader in enterprise-grade data analytics and AI solutions, committed to empowering businesses across various industries with cutting-edge technology and expert insights. Our core focus is on delivering advanced Data Analytics & AI Solutions. By combining sophisticated technology with subject matter expertise, we deliver material impact on our clients' topline and streamline their operations. We specialize in providing tailored solutions across financial services, CPG, legal, pharma, life sciences, retail and logistics, helping them build robust data analytics and AI capabilities. With a client base spanning 30 countries, Straive's strategically located teams operate from eight countries and is headquartered in Singapore. This global presence enables us to offer localized expertise with a worldwide perspective.

Join Straive to be part of a dynamic team at the forefront of data analytics and AI innovation. Here, you'll have the opportunity to contribute to transformative projects, supported by significant investments and an entrepreneurial drive fueled by our partnership with EQT.

Location: London, England, UK

Contract Type: Contractor

About the Role

We are seeking an experienced Data Science Consultant with a strong logistics/supply chain background to support our AMS (Advanced Management Solutions) initiatives. This is a hands-on consulting role: you will work closely with business stakeholders, understand operational processes, identify improvement opportunities, and deliver data-driven solutions. You must be equally comfortable talking to the business and working with data — able to translate operational challenges into analytical problems and turn insights into practical recommendations.

Key Responsibilities

• Consulting & Stakeholder Engagement
  • Engage with operations, logistics, and management teams to understand current processes, pain points, and strategic objectives.
  • Facilitate workshops, interviews, and process walkthroughs to map end-to-end logistics processes.
  • Translate business questions into clear analytical use cases and project plans.
  • Present findings, recommendations, and business cases to both technical and non-technical stakeholders.
• Process Understanding & Opportunity Mining
  • Analyse logistics and supply chain processes (e.g., transport, warehousing, inventory, last-mile, network design) to identify inefficiencies and improvement levers.
  • Quantify potential value (cost savings, service improvement, productivity gains) from data-driven interventions.
  • Prioritise opportunities based on impact, feasibility, and alignment with business strategy.
• Data Analysis & Data Science
  • Explore, clean, and model data from multiple sources (e.g., WMS, TMS, ERP, telematics, order and shipment data).
  • Build analytical and/or machine learning solutions (e.g., forecasting, optimisation, routing, capacity planning, performance analytics).
  • Develop clear metrics, dashboards, and reports to track performance and impact.
  • Work with data engineering/IT teams to ensure data availability, quality, and governance.
• Delivery & Change Support
  • Support the design and implementation of pilots and proof-of-concepts.
  • Document methodologies, assumptions, and solution designs.
  • Contribute to change management by explaining insights and solutions in business language and supporting adoption.

Required Experience & Skills

• Professional Experience
  • Proven experience in a data science, analytics, or advanced analytics role.
  • Demonstrable consulting experience (internal or external), including requirements gathering, stakeholder management, and presenting to senior audiences.
  • Logistics/supply chain experience is essential (e.g., 3PL, retail logistics, e-commerce fulfilment, transport, warehousing, network optimisation).
• Technical Skills
  • Strong proficiency in data analysis using tools such as Python and/or R.
  • Solid SQL skills for data extraction and manipulation.
  • Experience with data visualisation tools (e.g., Power BI, Tableau, Qlik, or similar).
  • Good understanding of statistical methods and/or machine learning techniques relevant to operations and logistics (e.g., forecasting, clustering, optimisation, simulation).
• Consulting & Business Skills
  • Ability to quickly understand complex operational processes and constraints.
  • Strong problem-structuring skills: can break down ambiguous problems into clear analytical workstreams.
  • Excellent communication skills, able to explain technical concepts in simple, business-focused terms.
  • Comfortable facilitating workshops, leading discussions, and challenging assumptions constructively.
  • Strong commercial mindset with the ability to quantify and articulate business value.
• Nice-to-Have
  • Experience with optimisation tools or libraries (e.g., OR-Tools, CPLEX, Gurobi).
  • Experience working with large-scale logistics datasets (e.g., route data, scan events, telematics, IoT).
  • Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and modern data platforms.
  • Prior experience in a consulting firm or as an internal consultant in a logistics-heavy organisation.

This job description is not intended to cover or contain a comprehensive listing of all responsibilities, duties, or activities that are required. Responsibilities, duties, and/or activities may change, or new ones may be added at any time with or without notice.

If you are a motivated professional with a passion for delivering impactful solutions, we’d love to hear from you. Apply today to be part of a dynamic and forward-thinking team at Straive.

Straive is an Equal Opportunity Employer. Our policy is clear: there shall be no discrimination based on age, disability, sex, race, religion or belief, gender reassignment, marriage/civil partnership, pregnancy/maternity, or sexual orientation. We are an inclusive organization and actively promote equality of opportunity for all with the right mix of talent, skills and potential. We welcome all applications from a wide range of candidates. Selection for roles will be based on individual merit alone.