data engineer

machine learning engineer

senior data scientist

financial analyst

senior data engineer

data scientist

<div>Role Overview
We are looking for a Data Scientist to transform raw industrial data into actionable insights and develop predictive models that address real-world energy and operational challenges. You will bridge advanced analytics and practical business impact by turning complex data into strategic decisions.
Key Responsibilities<ul><li>
Collect, clean, and preprocess structured and unstructured data from multiple sources
</li><li>Perform exploratory data analysis (EDA) to identify trends, correlations, and anomalies
</li><li>Develop, validate, and deploy machine learning and predictive models
</li><li>Design and maintain scalable data pipelines and automation workflows
</li><li>Translate business problems into analytical and statistical solutions
</li><li>Collaborate with engineering, product, operations, and leadership teams
</li><li>Present insights through dashboards, reports, and data visualizations
</li><li>Monitor model performance and continuously optimize algorithms
</li><li>Ensure data quality, integrity, governance, and security compliance</li></ul> 

Requirements 
<ul><li>
Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field
</li><li>2+ years of experience in data science, analytics, or machine learning roles
</li><li>Strong programming skills in Python (preferred) or R
</li><li>Proficiency in SQL and working with relational databases
</li><li>Experience with machine learning frameworks (Scikit-learn, TensorFlow, PyTorch)
</li><li>Solid understanding of statistics and probability
</li><li>Experience with data visualization tools (Power BI, Tableau, Matplotlib, etc.)
</li><li>Familiarity with cloud platforms (AWS, Azure, or GCP)
</li><li>Knowledge of big data tools such as Spark or Hadoop
</li><li>Understanding of MLOps concepts and model deployment workflows
</li><li>Strong analytical thinking and problem-solving abilities
</li>Excellent communication and collaboration skills 
<li>
</li></ul> 
 
Benefits 
<ul><li>
Annual bonus
</li></ul><ul><li>Health insurance and wellness programs
</li><li>Professional development and training opportunities</li></ul></div>

Data Scientist

Advansys Intelligent Solutions

<div>
 
 Role Overview
 
 
 
 We are looking for a
 
 Data Scientist
 
 to transform raw industrial data into actionable insights and develop predictive models that address real-world energy and operational challenges. You will bridge advanced analytics and practical business impact by turning complex data into strategic decisions.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Collect, clean, and preprocess structured and unstructured data from multiple sources
 </li>
 <li>
 Perform exploratory data analysis (EDA) to identify trends, correlations, and anomalies
 </li>
 <li>
 Develop, validate, and deploy machine learning and predictive models
 </li>
 <li>
 Design and maintain scalable data pipelines and automation workflows
 </li>
 <li>
 Translate business problems into analytical and statistical solutions
 </li>
 <li>
 Collaborate with engineering, product, operations, and leadership teams
 </li>
 <li>
 Present insights through dashboards, reports, and data visualizations
 </li>
 <li>
 Monitor model performance and continuously optimize algorithms
 </li>
 <li>
 Ensure data quality, integrity, governance, and security compliance
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field
 </li>
 <li>
 2+ years of experience in data science, analytics, or machine learning roles
 </li>
 <li>
 Strong programming skills in Python (preferred) or R
 </li>
 <li>
 Proficiency in SQL and working with relational databases
 </li>
 <li>
 Experience with machine learning frameworks (Scikit-learn, TensorFlow, PyTorch)
 </li>
 <li>
 Solid understanding of statistics and probability
 </li>
 <li>
 Experience with data visualization tools (Power BI, Tableau, Matplotlib, etc.)
 </li>
 <li>
 Familiarity with cloud platforms (AWS, Azure, or GCP)
 </li>
 <li>
 Knowledge of big data tools such as Spark or Hadoop
 </li>
 <li>
 Understanding of MLOps concepts and model deployment workflows
 </li>
 <li>
 Strong analytical thinking and problem-solving abilities
 </li>
 <li>
 Excellent communication and collaboration skills
 
 
 </li>
 </ul>
 
 Benefits
 
 
 
 <ul>
 <li>
 Annual bonus
 </li>
 <li>
 Health insurance and wellness programs
 </li>
 <li>
 Professional development and training opportunities
 </li>
 </ul>
</div>

RATP Dev

<div><h2 class="jobSectionHeader">Data Scientist</h2>
<div><ul><li><div>Fixed-term contract</div>
</li>
<li><div>Full-time</div>
</li>
<li><div>At least 2 years of experience (Junior level)</div>
</li>
<li><div>Bachelor degree</div>
</li>
<li><div>Data Manager/Expert</div></li></ul></div></div>
 <div><div><div><div><h2 class="jobSectionHeader">Mission
</h2><div>JOB PURPOSE:
The Data Scientist is responsible for leveraging data to generate insights, support decision-making, and enhance operational efficiency. The role focuses on analyzing complex datasets from various business systems (such as timetables, schedules, ridership data, and maintenance systems) and translating them into actionable intelligence. This includes developing data-driven models, creating dynamic visualizations, and collaborating with stakeholders to improve data adoption and utilization across the organization.</div></div><div>
<h2 class="jobSectionHeader">Profile
</h2><div>RESPONSIBILITIES/DUTIES
Data Science &amp; Analytics<ul><li> Perform data transformations, cleaning, and preprocessing to ensure quality and reliability.</li><li> Design, test, and implement machine learning and AI models to support predictive and operational needs.</li><li> Maintain and update a library of analytical tools, scripts, and programs.</li></ul>
Business Intelligence &amp; Visualization<ul><li> Design, develop, and maintain interactive dashboards and reporting solutions using Power BI, Qlik Sense, and other tools.</li><li> Build dynamic visualizations that support decision-making across operations and maintenance functions.</li><li> Document processes and maintain user guides to ensure smooth adoption of reporting solutions.</li></ul>
Collaboration &amp; Communication<ul><li> Partner with internal departments to define data needs, establish data streams, and enhance KPI tracking.</li><li> Liaise with software vendors and internal teams to ensure desired system features and performance are met.</li><li> Clearly communicate findings and explain complex concepts to both technical and non-technical stakeholders.</li></ul>
Continuous Improvement &amp; Knowledge Sharing<ul><li> Identify opportunities to restructure source data and influence the adoption of cleaner data structures.</li><li> Provide training sessions, short briefs, and knowledge-sharing activities to upskill colleagues.</li><li> Promote the use of company data tools, AI models, and portals to increase adoption and business value.</li></ul>
Safety Responsibilities<ul><li> Promote a positive safety culture within the workplace and attend any safety-related meetings or briefings as required within the job role.</li><li> Comply with the requirements of RDMC RQHSE Policy and Safety Management System.</li><li> Be mindful that Safety, Security, and Environmental protection are everyone&rsquo;s responsibility.</li><li> All staff members are accountable for reporting and intervening in any Safety, Security, or Environmental violations.</li></ul>
ESSENTIAL QUALIFICATIONS, KNOWLEDGE &amp; EXPERIENCE
Qualifications<ul><li> Bachelor&rsquo;s degree in Computer Science, Computer Engineering, Mathematics, or a related STEM field.</li><li> Additional certifications in Data Science, Machine Learning, AI, or data visualization technologies are an advantage.</li></ul>
Knowledge<ul><li> Proficiency in English; French is a plus.</li><li> Strong understanding of relational databases (SQL Server, MySQL, Oracle, etc.) with the ability to write queries.</li><li> Knowledge of data visualization and analytics concepts.</li><li> Ability to develop practical solutions using data.</li><li> Proficiency in Microsoft Office applications.</li></ul>
Experience<ul><li> 3&ndash;5 years of relevant experience in data science, software development, or data analysis.</li><li> Hands-on experience in programming (Python, C++ or similar).</li><li> Practical experience with data visualization tools (Power BI, Qlik, Excel).</li><li> Proven track record of delivering data science projects as a hands-on implementer.</li></ul>
DESIRED BEHAVIORS &amp; EXPERIENCES<ul><li> Demonstrates curiosity and persistence in identifying insights and creating business value.</li><li> Able to work independently and collaborate effectively within a team environment.</li><li> Communicates clearly and confidently, both verbally and in writing, to different audiences.</li><li> Show adaptability and flexibility when working with diverse stakeholders.</li><li> Strong problem-solving skills with the ability to manage competing priorities.</li><li> Takes initiative, meets deadlines, and shows accountability for results.</li></ul></div></div></div></div>
<div><div><div><h3 class="jobSectionHeader">Location</h3>
<div><div><div>Location</div></div>
<div>Address</div>
</div>Cairo, Cairo, Egypt</div></div></div></div><div></div>

MaxAB

<div>
 
 
 Company Description:
 
 
 
 MaxAB is re-engineering Africa's informal retail sector through a B2B e-commerce and fintech super app. Since launching in 2018, we've connected over 150,000 traditional retailers with suppliers, delivering 2.5+ million orders across Egypt and Morocco. Our fintech business now generates more revenue than e-commerce, with over $180 million in sales last year. Following our merger with Wasoko, we're expanding across Sub-Saharan Africa.
 
 
 
 
 
 
 About the Role:
 
 
 
 We are seeking a Data Scientist with a strong passion for data-driven problem-solving. In this role, you will combine technical expertise, analytical rigor, and business acumen to develop statistical and machine learning models, derive actionable insights, and support critical decision-making processes across the organization.
 
 
 
 
 
 
 What You&rsquo;ll Do :
 
 
 
 
 
 <ul>
 <li>
 Partner with diverse teams to design, implement, and analyze algorithms aimed at optimizing processes &amp; commercial operations.
 </li>
 <li>
 Apply robust statistical techniques to uncover relationships between variables, measure the impact of business strategies on key performance indicators, and build, validate, and maintain both statistical and machine learning models.
 </li>
 <li>
 Analyze large datasets to extract statistically valid and business-relevant insights. Ensure that findings are effectively translated into strategic recommendations.
 </li>
 <li>
 Continuously evaluate model performance and refine methodologies to enhance accuracy and reliability.
 </li>
 <li>
 Clearly articulate insights and complex statistical concepts to both technical and non-technical stakeholders, ensuring actionable intelligence is readily understood and applied.
 </li>
 </ul>
 
 
 
 <ul>
 <li>
 
 What We&rsquo;re Looking For :
 
 </li>
 </ul>
 
 
 Educational Background:
 
 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Computer Science, Statistics, or a related quantitative field.
 
 
 
 Professional Experience:
 
 
 <ul>
 <li>
 A minimum of
 
 
 3 years
 
 
 of experience in a data-focused role.
 </li>
 </ul>
 
 
 Technical Proficiency:
 
 
 <ul>
 <li>
 Proficient in Python and key libraries (e.g., Pandas, NumPy, Scikit-learn, Statsmodels, pytorch).
 </li>
 <li>
 Strong expertise in vectorization and code optimization for large-scale data processing.
 </li>
 <li>
 Advanced SQL skills for data querying and manipulation.
 </li>
 <li>
 Experience in Causal Inference &amp; Regression Analysis.
 </li>
 <li>
 Experience with Web &amp; App scraping, using Android studio or similar.
 </li>
 <li>
 Experience with NLP text matching.
 </li>
 <li>
 Experience with Deep Learning &amp; Deep Reinforcement Learning is a plus.
 </li>
 </ul>
 
 
 Analytical &amp; Statistical Expertise:
 
 
 <ul>
 <li>
 Solid understanding of business analytics, statistical analysis (including causal inference, simulation, regression, clustering), with an ability to translate complex data into actionable insights.
 </li>
 <li>
 Understanding of the FMCG &amp; Fintech market dynamics is a plus.
 </li>
 </ul>
 
 
 Data Visualization:
 
 
 <ul>
 <li>
 Familiarity with data visualization tools such as Tableau and Matplotlib.
 </li>
 </ul>
 
 
 Soft Skills:
 
 
 <ul>
 <li>
 Excellent problem-solving abilities, critical thinking, and the capacity to align technical solutions with broader business objectives. Strong communication skills are essential to effectively convey insights and drive decision-making.
 </li>
 </ul>
 
 
</div>

Data Scientist 1

RATP Dev Mobility Cairo

<div>
 
 Job Purpose
 
 
 
 The Data Scientist is responsible for leveraging data to generate insights, support decision-making, and enhance operational efficiency. The role focuses on analyzing complex datasets from various business systems (such as timetables, schedules, ridership data, and maintenance systems) and translating them into actionable intelligence. This includes developing data-driven models, creating dynamic visualizations, and collaborating with stakeholders to improve data adoption and utilization across the organization.
 
 
 
 Responsibilities/Duties
 
 
 
 
 Profil de candidat recherch&eacute; :
 
 
 
 
 Data Science &amp; Analytics
 
 
 
 <ul>
 <li>
 Perform data transformations, cleaning, and preprocessing to ensure quality and reliability.
 </li>
 <li>
 Design, test, and implement machine learning and AI models to support predictive and operational needs.
 </li>
 <li>
 Maintain and update a library of analytical tools, scripts, and programs.
 
 
 </li>
 </ul>
 
 Business Intelligence &amp; Visualization
 
 
 
 <ul>
 <li>
 Design, develop, and maintain interactive dashboards and reporting solutions using Power BI, Qlik Sense, and other tools.
 </li>
 <li>
 Build dynamic visualizations that support decision-making across operations and maintenance functions.
 </li>
 <li>
 Document processes and maintain user guides to ensure smooth adoption of reporting solutions.
 
 
 </li>
 </ul>
 
 Collaboration &amp; Communication
 
 
 
 <ul>
 <li>
 Partner with internal departments to define data needs, establish data streams, and enhance KPI tracking.
 </li>
 <li>
 Liaise with software vendors and internal teams to ensure desired system features and performance are met.
 </li>
 <li>
 Clearly communicate findings and explain complex concepts to both technical and non-technical stakeholders.
 
 
 </li>
 </ul>
 
 Continuous Improvement &amp; Knowledge Sharing
 
 
 
 <ul>
 <li>
 Identify opportunities to restructure source data and influence the adoption of cleaner data structures.
 </li>
 <li>
 Provide training sessions, short briefs, and knowledge-sharing activities to upskill colleagues.
 </li>
 <li>
 Promote the use of company data tools, AI models, and portals to increase adoption and business value.
 
 
 </li>
 </ul>
 
 Safety Responsibilities
 
 
 
 <ul>
 <li>
 Promote a positive safety culture within the workplace and attend any safety-related meetings or briefings as required within the job role.
 </li>
 <li>
 Comply with the requirements of RDMC RQHSE Policy and Safety Management System.
 </li>
 <li>
 Be mindful that Safety, Security, and Environmental protection are everyone&rsquo;s responsibility.
 </li>
 <li>
 All staff members are accountable for reporting and intervening in any Safety, Security, or Environmental violations.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 
 ESSENTIAL QUALIFICATIONS, KNOWLEDGE &amp; EXPERIENCE
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Computer Engineering, Mathematics, or a related STEM field.
 </li>
 <li>
 Additional certifications in Data Science, Machine Learning, AI, or data visualization technologies are an advantage.
 
 
 </li>
 </ul>
 
 Knowledge
 
 
 
 <ul>
 <li>
 Proficiency in English; French is a plus.
 </li>
 <li>
 Strong understanding of relational databases (SQL Server, MySQL, Oracle, etc.) with the ability to write queries.
 </li>
 <li>
 Knowledge of data visualization and analytics concepts.
 </li>
 <li>
 Ability to develop practical solutions using data.
 </li>
 <li>
 Proficiency in Microsoft Office applications.
 
 
 </li>
 </ul>
 
 Experience
 
 
 
 <ul>
 <li>
 3&ndash;5 years of relevant experience in data science, software development, or data analysis.
 </li>
 <li>
 Hands-on experience in programming (Python, C++ or similar).
 </li>
 <li>
 Practical experience with data visualization tools (Power BI, Qlik, Excel).
 </li>
 <li>
 Proven track record of delivering data science projects as a hands-on implementer.
 
 
 </li>
 </ul>
 
 Desired Behaviors &amp; Experiences
 
 
 
 <ul>
 <li>
 Demonstrates curiosity and persistence in identifying insights and creating business value.
 </li>
 <li>
 Able to work independently and collaborate effectively within a team environment.
 </li>
 <li>
 Communicates clearly and confidently, both verbally and in writing, to different audiences.
 </li>
 <li>
 Show adaptability and flexibility when working with diverse stakeholders.
 </li>
 <li>
 Strong problem-solving skills with the ability to manage competing priorities.
 </li>
 <li>
 Takes initiative, meets deadlines, and shows accountability for results.
 </li>
 </ul>
</div>

NoGood

<div>We are:
Goodie helps leading brands win AI search. As billions of people use ChatGPT, Perplexity, Gemini, and other AI systems to discover products and make buying decisions, brands need a way to understand and influence how they&rsquo;re represented.
Goodie gives teams a full AI control plane: real-time visibility into how AI models speak about their brand and products, how competitors show up, and an optimization engine to improve visibility and performance. This category didn&rsquo;t exist two years ago - we were early, and we&rsquo;re defining it.
We&rsquo;re backed by strong investors, trusted by category-leading customers, and scaling fast. We&rsquo;re hiring curious, ambitious builders to help shape the future of AI search.
We are looking for:
Goodie AI is searching for a talented and ambitious Data Scientist to join our growing team! Goodie helps brands win visibility and revenue across AI search, LLMs, and agentic commerce. You will be the point person turning messy multi-model signals into measurement, forecasts, and optimizations that our product can act on. If you enjoy building models that ship and change customer behavior, you will like this seat.
You&rsquo;ll do:<ul><li>
Work with large datasets. Own efficient querying, cleaning, labeling, and taxonomy alignment for brands, SKUs, and categories.</li><li>
Design sampling and classification strategies that turn noisy LLM outputs and crawler logs into reliable brand and product insights.</li><li>
Use LLMs and NLP to extract structure from unstructured text at scale. Topics include query fan-out, sentiment, citation extraction, and entity linking for brands, products, and creators.</li><li>
Define product-grade metrics. Create durable definitions for visibility score, answer coverage, product presence, and agentic checkout readiness.</li><li>
Build and run experimentation frameworks. A/B tests, holdouts, counterfactuals, and uplift modeling to quantify impact on citations, share of voice, and conversions.</li><li>
Develop and refine predictive models that analyze and forecast AI search behavior across models and surfaces.</li><li>
Translate complex findings into clear decisions. Partner with the founding team to inform roadmap, pricing, and customer playbooks.</li><li>
Create evaluation harnesses. Establish automatic evals and human-in-the-loop labeling for model quality, bias, and drift across LLM providers.</li><li>
Detect anomalies. Build monitors for crawler behavior, rankings, and feed health to catch regressions before customers do.</li></ul>
You have:<ul><li>
3 to 7 years in applied analytics or data science within tech, marketing, or ads. Startup or high-growth experience preferred.</li><li>
Strong Python and SQL. Comfortable in notebooks and in code reviews.</li><li>
Skilled with sampling and inference. Stratified sampling, bootstrapping, extrapolation, reweighting, and variance estimation.</li><li>
Solid ML toolkit. Time series, classification, regression, weak supervision, and methods to estimate event frequency from partial observations.</li><li>
Practical LLM knowledge. Strengths in prompt design, structured extraction, embeddings, and an understanding of model limits and failure modes.</li><li>
Curious and current on multi-modal and LLM research. You enjoy reading papers and pressure testing ideas in real data.</li><li>
Builder mindset in a fast team. You value clarity, speed, and ownership.</li></ul>
Nice to have:<ul><li>
Experience with large-scale information extraction or search quality</li><li>
Background in causal inference, MMM, or attribution models</li><li>
Hands-on work with product feeds and retail catalogs</li><li>
Contributions to open source or published work we can read</li><li>
Deployed side projects we can click through</li></ul>
Our data and modeling canvas:<ul><li>
Problems: AI search measurement, AEO scoring, agentic commerce readiness, product catalog and feed integrity, ranking and citation shifts, attribution for AI traffic</li><li>
Signals: LLM responses, crawler and agent logs, SERP and AI answer snapshots, product feeds, marketplace metadata, GA4 and GSC connectors, CRM data</li><li>
Targets: Share of voice, citation count, answer coverage, SKU presence, conversion lift, time-to-value for optimizations</li></ul>
Tech stack you will touch:<ul><li>
Languages: Python, SQL</li><li>
Libraries: pandas, NumPy, scikit-learn, PyTorch or TensorFlow, Hugging Face, spaCy.</li><li>
Data: Postgres or AlloyDB, BigQuery, dbt, DuckDB for local work</li><li>
Production ML/MLOps: model serving (FastAPI/Flyte/Batch jobs), CI/CD, versioning, experiment tracking (MLflow/Weights &amp; Biases), monitoring &amp; alerting for performance/drift.</li><li>
Cloud &amp; data tooling: AWS/GCP/Azure, containers (Docker).</li><li>
Models and providers: OpenAI, Anthropic, Google, Meta, Mistral, Perplexity, together with internal eval harnesses</li></ul>
BEWARE OF FRAUD! Please be aware of potentially fraudulent job postings or suspicious activity by persons that are posing as Goodie team members, recruiters, and HR employees. Our team will contact you regarding job opportunities from email addresses ending in @nogood.io or @higoodie.com. Additionally, we do utilize our ATS- Ashby- to help us schedule initial screening calls. Job seeking is hard- we&rsquo;re sorry that scammers have added this element to your search for something new. Stay vigilant out there!</div>

Dish'd

<div>
 
 Dish&rsquo;d is the UK&rsquo;s fastest-growing franchisor of virtual food brands. We partner with food operators to help them maximise their kitchen capacity by launching and scaling delivery-only brands across the UK.
 
 
 We&rsquo;re looking for a commercially minded Data Scientist to design and build predictive models that directly shape expansion, pricing, and operational decisions across a fast-growing, multi-brand food platform. This is not a reporting role. This is a modelling role.
 
 
 
 
 
 You will build forecasting systems from scratch, own experimentation frameworks, and influence real commercial strategy &mdash; from new site openings to pricing optimisation and franchise performance.
 
 
 
 
 
 
 The Role
 
 
 
 Forecasting &amp; Predictive Modelling (Core Focus)
 
 
 
 
 
 You will design and deploy predictive models that directly support growth and profitability, including:
 
 
 
 
 <ul>
 <li>
 Sales forecasting models for new site openings, brand placement, and territory expansion
 </li>
 <li>
 Demand forecasting at brand, location, and time-of-day level
 </li>
 <li>
 Pricing optimisation models to simulate revenue and margin impact
 </li>
 <li>
 Churn prediction models to identify at-risk franchise partners
 </li>
 <li>
 Customer lifetime value (CLV) and territory saturation analysis
 </li>
 <li>
 Inventory and cost optimisation modelling
 </li>
 </ul>
 
 You&rsquo;ll continuously refine and retrain models as new data becomes available, ensuring accuracy and commercial relevance over time.
 
 
 
 
 
 Experimentation &amp; Statistical Analysis
 
 
 
 
 
 You will own our experimentation framework, including:
 
 <ul>
 <li>
 Designing A/B and multivariate testing for menus, pricing, and marketing
 </li>
 <li>
 Geo-based experimentation across territories
 </li>
 <li>
 Rigorous statistical evaluation of test results
 </li>
 <li>
 Clear communication of findings with actionable recommendations
 </li>
 </ul>
 
 
 
 
 Automation &amp; Operational Analytics
 
 <ul>
 <li>
 Build automated monitoring and anomaly detection systems
 </li>
 <li>
 Integrate model outputs into dashboards and reporting workflows
 </li>
 <li>
 Support development of data pipelines feeding model inputs
 </li>
 <li>
 Evaluate and recommend AI-powered tools to improve forecasting accuracy
 </li>
 </ul>
 
 
 
 
 Collaboration &amp; Commercial Impact
 
 
 You&rsquo;ll work closely with the Data Lead and Data Engineer to ensure models are built on clean, reliable warehouse data. You&rsquo;ll also partner with Operations, Marketing, and Finance to translate business challenges into modelling opportunities &mdash; and communicate complex outputs in a clear, compelling way.
 
 
 Your work will feed directly into commercial strategy and board-level reporting.
 
 
 
 
 
 What We&rsquo;re Looking For
 
 
 
 Essential
 
 
 <ul>
 <li>
 3&ndash;5 years&rsquo; hands-on experience in applied data science or predictive analytics
 </li>
 <li>
 Proven experience building forecasting models from scratch in a commercial environment
 </li>
 <li>
 Strong Python skills (pandas, NumPy, scikit-learn, statsmodels, Prophet/NeuralProphet or similar)
 </li>
 <li>
 Deep experience in time series forecasting (ARIMA, SARIMA, Prophet, exponential smoothing, gradient boosting approaches)
 </li>
 <li>
 Experience building regression, classification, and clustering models
 </li>
 <li>
 Strong statistical foundation (hypothesis testing, A/B testing, confidence intervals, causal inference)
 </li>
 <li>
 Solid SQL skills
 </li>
 <li>
 Experience taking models from prototype to production (validation, monitoring, iteration)
 </li>
 <li>
 Excellent communication skills &mdash; able to translate complex outputs for non-technical stakeholders
 </li>
 <li>
 Fluency in spoken and written English (IELTS Level 8 / Cambridge C2 equivalent)
 </li>
 <li>
 Highly organised, detail-oriented, and self-motivated
 </li>
 </ul>
 
 Desirable
 
 <ul>
 <li>
 Experience with Power BI or similar BI tools
 </li>
 <li>
 Familiarity with workflow automation tools (Airflow, n8n, etc.)
 </li>
 <li>
 Cloud deployment experience (Azure, GCP, AWS)
 </li>
 <li>
 NLP / sentiment analysis experience
 </li>
 <li>
 Background in food delivery, QSR, logistics, or other fast-moving industries
 </li>
 <li>
 Google Apps Script / Sheets automation
 </li>
 <li>
 Git and collaborative development workflows
 </li>
 </ul>
 
 Why Join Us?
 
 <ul>
 <li>
 High commercial impact &mdash; your models will shape real expansion decisions
 </li>
 <li>
 Direct exposure to strategic planning and senior leadership
 </li>
 <li>
 Opportunity to build forecasting capability from the ground up
 </li>
 <li>
 Clear pathway to Lead Data Scientist as the team scales
 </li>
 <li>
 Fast-paced, high-growth environment where data drives decisions
 </li>
 </ul>
 
 
</div>

Applied Data  Scientist

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