IMPULSE LOGIC

About the Company

IMPULSE LOGIC delivers a cloud-based replenishment solution for retailers everywhere. Designed and built by retailers, our AI and smart algorithms transform the last footsteps of the supply chain, from truck to shelf, into impactful store performance opportunities, delivering great product availability. Our solution solves your last-yard inventory challenges, enabling you to sell more, waste less and deliver an outstanding experience, for customers & store teams. Our flexible, intuitive and easy-to-execute platform helps you develop and maintain a culture that’s devoted to customer success. Availability - transforming shelf replenishment to ensure uninterrupted on-shelf availability, enabling customers to find what they want, when they need it - both in store and online Efficiently - optimizing the journey from truck to shelf every time, based on proactive alerts, ensuring teams are clear on the right tasks to complete at the right time Consistently - embracing an intelligent future, powered AI and smart algorithms, our intuitive and easy-to-execute platform drives consistent execution and real bottom-line results every time Experience Availability. Experience Impulse Logic. Learn more about how we can help your retail business at impulselogic.com

Listed Jobs

Company Name

IMPULSE LOGIC

Job Title

Data Scientist

Job Description

**Job title:** Data Scientist **Role Summary:** Develop and deploy predictive analytics and machine‑learning solutions that directly influence business decisions for a cloud‑based retail replenishment platform. Build end‑to‑end MLOps pipelines, create interactive dashboards, and collaborate with business stakeholders to translate model outputs into operational tools. **Expectations:** - Deliver high‑accuracy predictive models (e.g., labor forecasting, inventory optimization, demand planning). - Translate analytical insights into actionable tools and dashboards accessible to non‑technical users. - Maintain production pipelines with continuous monitoring, version control, and performance updates. - Communicate findings clearly to technical teams and C‑suite executives. **Key Responsibilities:** 1. **Model Development** – design, build, and validate predictive models using ERP data (SAP, Microsoft Dynamics, custom feeds) and large enterprise datasets. 2. **MLOps & Deployment** – implement cloud‑based ML pipelines (Azure ML preferred, AWS SageMaker optional), including data preprocessing, feature engineering, model training, versioning, monitoring, and CI/CD. 3. **Dashboard & Tool Creation** – develop interactive dashboards (Tableau, Power BI, Grafana) and optimization engines that showcase predictions and recommendations. 4. **Stakeholder Collaboration** – work closely with business analytics teams and executives to understand challenges, define metrics, and refine model outputs. 5. **Continuous Improvement** – conduct A/B testing, statistical analysis, and incorporate feedback loops to improve model performance and relevance. 6. **Advanced Analytics** – explore NLP, sentiment analysis, customer analytics, and supply‑chain analytics as needed. **Required Skills:** - 3+ years of applied data science in business or enterprise settings. - Strong Python stack: Pandas, NumPy, scikit‑learn, PyTorch/TensorFlow. - SQL proficiency and experience handling large, complex datasets. - Experience with ERP integration and analytics (SAP, Microsoft Dynamics, POS, BOH). - Predictive modeling and time‑series forecasting. - MLOps tools: Azure ML, SageMaker, Git, CI/CD pipelines. - Dashboard development: Tableau, Power BI, Grafana, or equivalent. - Statistical analysis, A/B testing, and version control. - Effective communication to non‑technical audiences. **Required Education & Certifications:** - Bachelor’s degree (or higher) in Computer Science, Statistics, Mathematics, Engineering, or related field. - Azure Machine Learning Data Scientist certification or equivalent credentials highly preferred. ---

Manchester, United kingdom

Hybrid

Junior

12-12-2025