Metal Insight Analyst

Kpler

At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors. Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 700 experts from 35+ countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success.

Awin

Purpose of the Position Data is at the core of the company’s decision‑making and commercial success. Our mission is to ensure that Awin leverages the full value of its data assets to drive strategic insight, optimise campaign performance, and empower client‑facing teams with best‑in‑class intelligence. We are looking for an experienced Analytical Engineer to join our BI team and shape the data foundation that powers self-serve analytics across the business. This is an exciting opportunity to establish our Analytical Engineering practice from scratch, working on a modern Databricks stack with Tableau and Power BI as our primary BI tools. This role sits at the intersection of Data Engineering and BI. You will work closely Data Engineering who own our data pipelines, Databricks infrastructure and data intelligence, and with BI Developers and Insight Analysts who deliver reporting and insight to stakeholders. The purpose of this role is to bridge both worlds, taking reliable data from our reporting layer and transforming it into a trusted, well-documented semantic layer that the whole team can build from. The ultimate goal is to successfully unlock self serve reporting across the organisation. Key Tasks & Accountabilities Build the Analytics Engineering practice * Provide the business context for the mart layers of our data architecture, feeding into BI-ready tables that support self-serve analytics across the business. * Create a single source of truth for business metric definitions - KPIs, business logic, and calculation rules. This should be accessible to all BI tools. * Take responsibility for data quality initiatives and own documentation around the semantic layer. Work across teams * Partner with Data Engineering to agree handoff boundaries, raise upstream data requirements, and flag quality issues at source. * Work with Insight Analysts to encode business logic and stakeholder requirements into reliable, reusable data models. * Support BI Developers in consuming the semantic layer efficiently within Tableau and Power BI. * Participate in regular cross-departmental syncs with Data Engineering to keep both teams aligned. Upskill and develop the team * Work closely with the BI Manager to coach BI Developers in Analytics Engineering best practices considering tools such as dbt * Create clear documentation and playbooks so that team members can contribute to any dbt project independently. * Be an internal advocate for Analytics Engineering standards across both the BI team and Data Engineering. Drive self-serve analytics * Design data marts with self-serve usage in mind. Clear naming, consistent grain, reliable refresh cadence. * Work with Insight Analysts to identify which stakeholder questions can be answered via self-serve and model accordingly. * Reduce ad-hoc data requests by making well-structured, trustworthy data accessible to the business. * Ensure the semantic layer is AI-ready. Clean, governed, and documented so that AI and GenAI tools can operate on our data without ambiguity.   Skills & Expertise * Strong, hands-on SQL. Comfortable writing complex transformations, optimising queries, and reviewing others’ code. * Proven experience with dbt (Core or Cloud) in a production environment. * Experience working with a cloud data warehouse or lakehouse. Databricks preferred, but others also relevant (Snowflake, BigQuery etc) * Solid understanding of data modelling concepts: dimensional modelling, star schemas, and slowly changing dimensions. * Comfortable working in a code-reviewed, version-controlled workflow. * Experience working alongside or within a BI team. Understanding what BI Developers and Insight Analysts need from the data layer. * Ability to translate ambiguous business requirements into clear, well-documented data definitions. * Strong communication skills. Able to explain technical concepts to non-technical stakeholders and align across departments. Highly desirable * Experience with Tableau and/or Power BI and an understanding of how BI tools consume data models. * Familiarity with Databricks specifically, including Delta Lake and notebook-based development. * Experience with semantic layer or governance tooling. Unity Catalog, dbt Semantic Layer, Cube, or similar. * Experience mentoring or upskilling colleagues in data tooling. * Exposure to data observability or data quality tooling. * Exposure to AI or GenAI data requirements. Understanding of what makes data AI-ready.   Our Offer * Flexi-Week and Work-Life Balance: We prioritise your mental health and wellbeing, offering you a flexible four-day Flexi-Week at full pay and with no reduction to your annual holiday allowance. We also offer a variety of different paid special leaves. * Flexi-Office: We offer an international culture and flexibility through our Flexi-Office and hybrid/remote work possibilities to work across Awin regions * Health & Well Being: With our support and access to various initiatives and sports offers, you can devote yourself to your mental and physical well-being. . * Development: We’ve built our extensive training suite Awin Academy to cover a wide range of skills that nurture you professionally and personally, with trainings conveniently packaged together to support your overall development. * Remote Working Allowance: You will receive a monthly allowance to cover a part of your running costs. In addition, we will support you in setting up your remote workspace appropriately. * Appreciation: Thank and reward colleagues by sending them a voucher through our peer-to-peer program. * We are hiring in multiple countries, additional benefits in terms of health, well being, security and more will be discussed further upon first initial interview with the talent team. Established in 2000, Awin is proud of our dynamic, social and inclusive culture. Like all businesses, we’ve had to adapt and nurture our culture in a virtual environment. Our virtual ‘Life @ Awin’ hub brings our colleagues from across the globe together for various social activities. Diversity & Inclusion are paramount to us, and we proudly pursue and hire diverse team members. We champion uniqueness and authenticity; this is who we are at our core. Our network of affiliate partnerships are diverse and transparent, as are the employees powering our vision to build the world’s leading open partner ecosystem. We welcome all backgrounds, identities, and experiences. If you need support at any point in the application or interview process, please let us know. Awin is part of the Axel Springer group. Learn more at axelspringer.com/en/, and explore the Axel Springer Essentials here: axelspringer.com/en/inside/the-essentials-what-we-have-adapted-and-why   Apply now to begin the next stage of your career at a progressive company that supports both your professional and personal development.

Multiverse

Multiverse is the upskilling platform for AI and Tech adoption. We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce. Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance. In April 2026, we announced $70 million in strategic funding, led by Schroders Capital, with participation from StepStone Group, Lightspeed Venture Partners and General Catalyst. At an increased valuation of $2.1bn, the round makes us Europe’s first EdTech double unicorn. But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output. Join Multiverse and power our mission to equip the workforce to win in the AI era. WHAT WE NEED: At Multiverse, the models we build don't just sit in notebooks - they drive the decisions that shape our business every day. From predicting learner outcomes to forecasting operational demand and optimising how we allocate resources, this work sits at the very core of how we run the company. As a Senior Data Scientist, you'll own these models end to end. You'll develop a deep understanding of how Multiverse operates across our customer, learner and operational domains - and translate that understanding into rigorous, production-grade ML models that genuinely move the needle. To be successful, you'll be comfortable getting hands-on with pipelines and infrastructure - and unafraid of the statistical rigour that serious modelling demands. You'll work closely with stakeholders across every part of the business - helping them ask better questions, understand the answers, and act on them with confidence. Our leaders will make multi-million dollar decisions based on your recommendations, and our AI-powered product will decide how to support learners based on your models. You'll sit within our Data & Insight team, working day-to-day alongside Data Engineers, Data Product Developers and Insight Analysts. WHAT YOU'LL FOCUS ON: Business Understanding & Problem Definition * Building genuine expertise in how Multiverse operates across customer, learner and operational domains - becoming a trusted thought partner * Translating complex and often ambiguous business questions into well-scoped modelling problems with clear success criteria * Identifying where predictive, forecasting or optimisation models can have the greatest business impact, and prioritising accordingly Modelling & Statistical Analysis * Designing, developing and iterating supervised and unsupervised ML models that predict, forecast and optimise across the business * Applying rigorous statistical methods to ensure models are robust, unbiased and genuinely causal wherever causal claims are being made * Developing a deep understanding of our data landscape - its lineage, quirks, and limitations - and designing approaches that account for them * Monitoring and refining models over time, ensuring they remain accurate and relevant as the business evolves Data Engineering & Infrastructure * Collaborating closely with Data Engineers to build and maintain the data pipelines and ML infrastructure needed to develop and deploy your models * Productionising models to run reliably at scale, adhering to software engineering best practices - including version control, CI/CD and vulnerability management * Evaluating and implementing scalable approaches to data collection and processing, ensuring robust practices are in place WHAT WE'RE LOOKING FOR: Required * 5+ years of data science/machine learning experience, with a proven track record building and deploying models that drive real business decisions * Deep expertise in predictive modelling, forecasting and/or optimisation - with strong command of the underlying statistical principles * Strong proficiency in Python and core ML libraries (e.g., NumPy, Pandas, Scikit-Learn, xgboost, shap) * Advanced working knowledge of SQL * Hands-on experience with data pipelines and ML infrastructure * Experience working within AWS (ideally using Sagemaker) and/or Azure * Comfort working across our data stack - inc Airflow, Snowflake * Experience with version control and CI/CD practices (ideally using GitHub) * Rigorous attention to statistical validity - comfortable challenging assumptions and defending methodology * Understanding of best practices in data protection and information security Desirable * Experience with causal inference methods (e.g., diff-in-diff, instrumental variables, propensity score matching) * Experience with dbt for data transformation * Knowledge of infrastructure as code tools (e.g. Terraform) * Strong professional and/or academic background within a highly quantitative discipline (e.g. statistics, mathematics, physics or economics) Benefits * Time off - 27 days holiday, plus 5 additional days off: 1 life event day, 2 volunteer days, 2 company-wide wellbeing days (M-Powered Weekend) and 8 bank holidays per year * Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Wellhub and access to Spill - all in one mental health support * Hybrid work offering - for most roles we collaborate in the office three days per week with the exception of Coaches and Instructors who collaborate in the office once a month * Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year * Space to connect: Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that’s always stocked! Our Commitment to Diversity, Equity and Inclusion We’re an equal opportunities employer. And proud of it. Every applicant and employee is afforded the same opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. This will never change. Read our Equality, Diversity & Inclusion policy here. Our Commitment to Safeguarding Multiverse is committed to safeguarding and promoting the welfare of our learners. We expect all employees to share this commitment and adhere to our Safeguarding Policy, our Prevent Policy and all other Multiverse company policies. Successful applicants will be required to undertake at least a Basic check via the Disclosure Barring Service (DBS). For roles that will involve a Regulated Activity, successful applicants must also undergo an Enhanced DBS check, including a Children’s Barred List check and a Prohibition Order check. Roles involving Regulated Activity may interact with vulnerable groups, therefore are exempt from the Rehabilitation of Offenders Act 1974 meaning applicants are required to declare any convictions, cautions, reprimands, and final warnings. Providing false information is an offence and could result in the application being rejected or summary dismissal if the applicant has been selected, and possible referral to the police and the DBS.