Ekimetrics

About the Company

Ekimetrics is a pioneering leader in data science and AI-powered solutions for sustainable business performance.

We help companies get more from their data and implement pre-packaged AI solutions, so they can combine high impact with long-term business purpose.

A focus on impact - steered by purpose

Ekimetrics works with many of the world's leading businesses to accelerate their transformation to sustainability through the application of data science and artificial intelligence.

We are uniquely specialized in creating scalable data and analytics solutions that drive high-impact optimizations in alignment with overarching brand strategy and sustainability goals.

Our goal: Enable our clients to pursue practical short-term gains combined with long-term value creation.

Since 2006 we've pioneered the use of AI and advanced data science applied to unified marketing measurement, holistic business optimization and broad-ranging sustainability goals. In particular, we've specialized in using its strengths in balancing multiple constraints in order to reconcile financial KPIs with non-financial goals.

A business-first approach to solutions delivery

All our 400 data experts and industry specialists work together in integrated squads. We value specific industry and domain expertise and focus on practical solutions in use. This is why we don't outsource execution: so we can reduce the time to results while maintaining quality, believing in a high-service approach. We maintain our own data science platform, and a collection of pre-packaged solutions that we use to provide insights and to deploy scalable solutions faster.

Key figures:
* 400 data experts
* 1,000+ data science projects
* 50+ countries in which we deliver projects
* 4 offices worldwide

Visit us at ekimetrics.com.

Listed Jobs

Company Name

Ekimetrics

Job Title

Stage 2026 Data Scientist - Marketing and commercial effectiveness(H/F/N)

Job Description

**Job Title** Stage 2026 Data Scientist – Marketing and Commercial Effectiveness (H/F/N) **Role Summary** Internship for a data science student with strong technical and marketing acumen. Supports the analytics team in transforming client data into actionable marketing strategy and media optimization insights, using econometrics, statistical modeling, and programming. **Expectations** - Complete internship from September or October 2026. - Deliver analytical outputs and client‑facing recommendations. - Collaborate across cross‑functional teams (Product, Strategy, Consulting). - Demonstrate proactive communication, analytical curiosity, and adaptability. **Key Responsibilities** 1. Data handling: extract, clean, and transform large datasets using Python and Excel. 2. Build and validate econometric, Bayesian, and other statistical models. 3. Conduct marketing analytics: media mix modeling, attribution, and performance forecasting. 4. Translate model outputs into strategic recommendations for clients. 5. Participate in deliverable creation and client presentations. 6. Engage in continuous learning and knowledge sharing within the team. **Required Skills** - Strong programming foundation in Python (pandas, numpy, scikit‑learn, statsmodels). - Knowledge of econometrics, statistical inference, and Bayesian methods. - Experience with data manipulation, cleaning, and visualization. - Ability to translate analytical findings into clear, actionable business insights. - Good communication and teamwork skills. - Familiarity with Databricks, Azure, or similar cloud data platforms is an advantage. **Required Education & Certifications** - Currently enrolled or recently graduated from a general engineering school or business school with a focus on data science, economics, statistics, or mathematics. - No mandatory certifications required; coursework or projects involving data science, econometrics, or marketing analytics is preferred.

Paris, France

Hybrid

19-12-2025

Company Name

Ekimetrics

Job Title

Manager - Business Data Science – Marketing & Commercial Effectiveness (H/F/N)

Job Description

**Job Title** Manager – Business Data Science, Marketing & Commercial Effectiveness **Role Summary** Lead the design, implementation, and delivery of data‑driven marketing and commercial effectiveness solutions for enterprise clients. Own client engagements from audit to production, shape internal analytics platforms, mentor junior consultants, and drive business development and thought leadership activities. **Expectations** - Deliver actionable, high‑impact marketing analytics and recommendations on time and budget. - Build and deepen strategic client relationships, identifying and expanding commercial opportunities. - Elevate the quality and scalability of internal data‑science solutions and standards. - Foster the growth of junior team members through coaching, training, and performance management. - Represent the firm at conferences, webinars, and pre‑sales events to showcase innovative capabilities. **Key Responsibilities** - Manage end‑to‑end data‑marketing projects: audit, planning, design, development, implementation, and maintenance. - Define and execute roadmaps for analytical architecture and data‑industrialisation cycles. - Present strategic insights and recommendations to senior client stakeholders. - Continuously improve internal analytics tools, contribute to best‑practice documentation, and drive operational excellence. - Lead community activities: knowledge sharing, technology scouting, and maintaining state‑of‑the‑art expertise. - Design and deliver technical training sessions (e.g., Eki.Academy) for internal staff. - Participate in recruitment, onboarding, and team expansion efforts. - Support pre‑sales activities: proposal development, solution scoping, and client workshops. - Act as a speaker or panelist at industry conferences and specialized tech events. **Required Skills** - Strong analytical and quantitative expertise; proven ability to guide consulting teams. - Excellent client‑relationship management and business development acumen. - Demonstrated experience managing complex, multi‑project programs. - Strategic thinking with deep sector knowledge in marketing, commerce, or related fields. - Creative problem‑solving, rigorous methodology, and persistence in challenging environments. - Solid business sense: ability to link data insights to commercial performance. - High emotional intelligence, active listening, and collaborative leadership style. - Outstanding written and verbal communication; ability to convey technical concepts to non‑technical audiences. **Required Education & Certifications** - Master’s degree or PhD in Data Science, Statistics, Computer Science, Business Analytics, Economics, or a related quantitative discipline. - Minimum 5 + years of professional experience in data‑driven marketing, commercial analytics, or AI consulting. - Proven track record with advanced analytics/ML tools (Python, R, SQL, cloud platforms). - Preferred certifications: PMP or equivalent project‑management credential; cloud or AI certifications (AWS, GCP, Azure) are a plus.

Paris, France

Hybrid

23-12-2025

Company Name

Ekimetrics

Job Title

2026 Summer Internship (6 Months) - Data Science & Marketing Effectiveness, London

Job Description

Job title: Summer Internship – Data Science & Marketing Effectiveness (6 Months) Role Summary: A 6‑month hybrid internship combining data science, statistical modelling and consulting on global client marketing performance projects. Interns will analyse large datasets, build marketing mix models, develop forecasting and segmentation tools, and translate analytical insights into actionable client recommendations. Expactations: • Full‑time availability 5 days a week from June/July 2026 to December 2026. • Hybrid working with a minimum of 2 days in the office per week. • Right to work in the UK (no sponsorship). • Active participation in client meetings, internal R&D, and team events. Key Responsibilities: • Analyse large marketing datasets using statistical techniques; extract key insights and present findings. • Build and maintain marketing mix models (MMM), testing frameworks, forecasting tools, and customer segmentation models. • Clean, process and manipulate data in Python (Pandas, PySpark, VS Code) and Excel (VLOOKUP, INDEX‑MATCH, pivot tables, SUMIFS, etc.). • Develop machine‑learning or econometric models and support model validation. • Translate complex analytical outputs into clear, client‑ready recommendations; present to stakeholders. • Collaborate cross‑functionally on deliverables, client meetings, and internal knowledge sharing. • Lead an independent research project aligned with business goals; present results to leadership. • Attend trainings, mentoring sessions, and contribute to a collaborative team culture. Required Skills: • Quantitative degree (Economics, Maths, Engineering, Computer/Data Science, Statistics, or equivalent). • Proficiency in Excel data manipulation (VLOOKUP, INDEX‑MATCH, pivot tables, SUMIFS, etc.). • Programming experience in Python or R; familiarity with Pandas, PySpark, and data‑cleaning pipelines. • Solid foundation in statistics, econometrics, and data‑analysis techniques. • Strong analytical thinking, attention to detail, and comfort with ambiguity. • Excellent written and verbal communication; ability to explain technical concepts to non‑technical stakeholders. • Highly collaborative, self‑motivated, organized, and eager to learn at the intersection of data and business. Required Education & Certifications: • Current student or recent graduate with a bachelor’s (or higher) in a quantitative discipline. • No specific certifications required, though familiarity with analytics tools (Power BI, Databricks, Git, Jira) is a plus.

London, United kingdom

On site

07-01-2026

Company Name

Ekimetrics

Job Title

Stage 2026 - Data Science et Machine Learning/AI practitionner - Sujet : Data attribution (H/F/N)

Job Description

**Job Title** Data Science & Machine Learning/AI Practitioners Internship – Data Attribution **Role Summary** Internship (6–12 months) focused on researching and implementing data attribution techniques for machine‑learning and deep‑learning models, with the aim of integrating findings into production pipelines. Works closely with the Innovation team on cutting‑edge research and industrial deployment of attribution methods. **Expectations** - Final‑year engineering or Master 2 student (or recent graduate) with strong foundations in machine learning and deep learning. - Proven ability to conduct literature reviews, prototype algorithms, and systematically evaluate open‑source solutions. - Comfortable writing clean, well‑tested Python code and collaborating with engineering experts. - Fluent in English (reading, writing, speaking). **Key Responsibilities** - Conduct comprehensive literature reviews on data attribution methods. - Evaluate and benchmark relevant open‑source libraries and proven techniques. - Apply attribution methods to classical ML models (XGBoost, LightGBM) and deep‑learning models for tabular (TabPFN, TabICL) and text data (Mistral, Gemma). - Investigate business use cases such as labeling‑error detection, model diagnostics, and model interpretation. - Develop modular, unit‑tested code and maintain version control (Git). - Collaborate with solution experts to industrialize prototypes and prepare them for deployment. - Share research findings and best practices with the Innovation team. **Required Skills** - Advanced proficiency in Python; experience with PyTorch, NumPy, scikit‑learn. - Solid understanding of machine‑learning algorithms (tree‑based, gradient boosting, tabular/text DL). - Strong background in probability, statistics, and linear algebra. - Familiarity with software development best practices: versioning (Git), unit testing, continuous integration. - Basic knowledge of interpretability/explanatory techniques (SHAP, LIME, Integrated Gradients, Deep SHAP, feature importance). - Excellent analytical, research, and communication skills. - English fluency (reading, writing, speaking). **Required Education & Certifications** - Current enrolment or recent graduation from an accredited engineering school or master’s program in Computer Science, Data Science, Statistics, Mathematics, or a related field. - Coursework or thesis work in machine learning, deep learning, probabilistic modeling, and data science. - No mandatory certifications; experience with ML frameworks and version control considered a plus.

Paris, France

Hybrid

20-01-2026