Data Scientist
Role details
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Tech stack
Job description
Data Scientist - Remote (UK) Want your models to ship, your ideas to shape products, and your work to solve real, high impact problems? If you're craving a role where your data science expertise genuinely changes how products are built and decisions are made… this is..., (Sr.) Economist / Data Scientist - EMEA Macro Consulting - Belfast Department:Macro ConsultingEmployment Type:Full TimeLocation:Belfast, UKDescription Oxford Economics, a leading economic forecasting and consulting firm, is seeking a motivated and ambitious Economist or..., A prominent AI and data science organization in Belfast is seeking a Senior Lead Data Scientist to take ownership of complex machine learning programs while guiding and supporting a developing data science team. The successful candidate will have over 8 years of experience..., A cybersecurity solutions company is seeking a Data Engineer/Scientist to drive innovative data use across platforms. The role focuses on developing data pipelines, participating in system design, and leading projects to enhance product security. Ideal candidates should..., Data Scientist - Credit Risk Up to £75,000 Remote (UK Based) The Company They are a global, fully remote fintech working across payments and credit risk. Their teams operate internationally collaborating on high impact risk and credit solutions. They use Python, SQL and...
Requirements
ways that drive decisions. Collaborate directly with clients and senior team members-understand business problems, formulate the right analytical questions, and contribute to insights that create measurable value.# Required Qualifications 2+ years (3+ years for Sr. Associate) of hands-on experience conducting data science and advanced analytics-not just ad-hoc analysis, but structured analytical projects that drove business decisions. You've framed problems, developed hypotheses, analyzed data, and delivered insights that created measurable impact. Strong Python and SQL programming skills with deep experience in the data science ecosystem (Pandas, NumPy, Scikit-learn, statsmodels, visualization libraries). Comfortable writing clean, reproducible code, not just notebooks. Solid foundation in statistics and machine learning: hypothesis testing, regression analysis, classification, clustering, experimental design, and understanding of when different approaches are appropriate for different questions. Experience with deep learning and modern neural architectures-understanding of transformer models, embeddings, and how to leverage foundation models for analytical tasks. You know when ML approaches add value over classical methods. Proficiency with data platforms: Microsoft Fabric, Snowflake, Databricks, or similar cloud analytics environments. You're comfortable working with large datasets and can write efficient queries. Strong visualization and rapid data application development skills-proficiency with programmatic visualization libraries (Plotly, Altair) and AI-assisted rapid application development using Cursor, Lovable, v0, or similar tools. You can quickly build interactive data interfaces that bring analyses to life. Ability to communicate technical concepts to non-technical stakeholders and work effectively with cross-functional teams. Strong data storytelling skills are essential. Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or related quantitative field (or equivalent practical experience). Flexibility to work in a hybrid model with periodic travel to client sites as needed.# Preferred Qualifications Experience in Financial Services, Manufacturing, or Energy & Utilities industries. Background in experimental design, A/B testing, and causal inference methodologies-including propensity score matching, difference-in-differences, or instrumental variables. Hands-on experience with deep learning frameworks (PyTorch, TensorFlow) and neural architectures-including transformers, attention mechanisms, and fine-tuning pretrained models for NLP, time-series, or tabular data applications. Experience building AI-assisted analytical workflows-leveraging foundation model APIs, vector databases, and retrieval systems to accelerate insight extraction from unstructured data. Experience with Bayesian methods, probabilistic programming (PyMC, NumPyro), or uncertainty quantification in business contexts. Experience with time-series analysis, forecasting methods (ARIMA, Prophet, neural forecasting), and demand planning applications. Cloud certifications (Azure Data Scientist, Databricks ML Associate, AWS ML Specialty). Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new problem spaces. Master's degree or PhD in Statistics, Applied Mathematics, Economics, or related quantitative field.# Why HuronVariety that accelerates your growth. In consulting, you'll work across industries and analytical challenges that would take a decade to encounter at a single company. Our Commercial segment spans Financial Services, Manufacturing, Energy & Utilities, and more-each engagement is a new domain to master and a new problem to crack.Impact you can measure. Our clients are Fortune 500 companies making significant investments in analytics and AI. The insights you generate will inform real decisions-pricing strategies, customer segmentation