At a Glance
- Tasks: Lead hands-on analytics and AI/ML to drive measurable sales growth.
- Company: Dynamic company focused on data-driven decision making in sales.
- Benefits: Competitive salary, flexible working options, and opportunities for professional development.
- Other info: Join a collaborative team with a focus on innovation and career advancement.
- Why this job: Make a real impact by transforming data into actionable insights for sales success.
- Qualifications: Experience in coding, analytics, and stakeholder management required.
The predicted salary is between 100000 - 150000 £ per year.
Hands-on Sales Analytics leader who turns Markets Sales growth opportunities into production analytics and AI/ML capabilities with clear KPI outcomes, strong governance, and senior stakeholder alignment.
Key role highlights
- Commercial-impact role focused on measurable Sales outcomes (uplift, win-rate, pipeline velocity, wallet share, and coverage productivity).
- Hands‐on expectation to code and prototype, contributing production‐grade analytics/ML components (not only oversight).
- Own use‐case pipeline from idea to scaled adoption, with KPI definition, testing/experimentation, and benefits tracking.
- Build on modern data/ML platforms (e.g., Databricks/Spark and Snowflake) with CI/CD, monitoring, and operational controls.
- Operate in a controlled environment with strong model governance (model risk, compliance, and controls).
- Partner with senior stakeholders across Sales, Product, Risk/Compliance, CDO/CTO, SMAD/Quants, and engineering to secure decisions and deliver outcomes.
Purpose of the role
As Director – Sales Analytics, you will use data, analytics, and hands‐on AI/ML to deliver measurable commercial impact across Markets Sales (e.g., revenue uplift, conversion/win rate, pipeline velocity, wallet‐share growth, and coverage productivity). You will build a prioritised pipeline of high‐value use cases across the opportunity lifecycle (e.g., targeting, next‐best action, and coverage effectiveness) and take them from discovery through deployment and adoption using trusted data, strong model governance, and hands‐on engineering. You will lead senior stakeholders across Sales, Product, Risk and Compliance, partnering with CDO/CTO, SMAD/Quants, and engineering/data teams to align priorities, secure decisions, and deliver outcomes.
To enable data‐driven strategic and operational decision making through extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualisations and reports.
Key responsibilities
- Deliver Markets Sales commercial impact with hands‐on analytics and AI/ML (uplift, win‐rate, pipeline velocity, wallet share, coverage productivity).
- Build a prioritised use‐case pipeline (targeting, next‐best action, coverage effectiveness) and ship to production with KPI definition and tracking.
- Engineer end‐to‐end solutions, personally coding/prototyping critical components from data prep and features to modelling, productionisation, monitoring, and support.
- Operationalise analytics/ML with trusted data, model governance, and delivery controls (CI/CD, deployment, monitoring) on Databricks/Spark and Snowflake.
- Lead senior stakeholders (Sales, Product, Risk/Compliance, CDO/CTO, SMAD/Quants, engineering/data) to align priorities, secure decisions, and deliver outcomes.
Essential candidate skills
- Demonstrated ability to deliver analytics and AI/ML end‐to‐end, writing production‐grade code from problem framing through build, deployment, and adoption.
- Demonstrated ability to engineer trusted data and features (quality, lineage, reusable metrics) using Python/SQL on Databricks/Spark and Snowflake.
- Demonstrated ability to apply engineering discipline to analytics/ML (Git, automated testing, code review, and CI/CD) to ship reliable changes.
- Demonstrated ability to prioritise use cases with clear KPIs and run experiments that evidence commercial impact.
- Demonstrated ability to influence senior stakeholders and deliver at scale within governance (model risk, compliance, and controls).
Desirable skills (optional)
- Markets Sales analytics use cases (targeting, next‐best action, coverage effectiveness, pipeline) plus market data and pre/post‐trade analytics; Kafka and dbt exposure a plus.
- Hands‐on coding in Python, SQL, and PySpark for pipelines and production analytics/ML; Java/C++ or kdb+/q a bonus.
- MLOps in a controlled environment: MLflow, registry/versioning, CI/CD (GitLab/Jenkins), drift/performance monitoring, documentation.
- Data governance practices and tooling: data quality checks, lineage/metadata, access controls, and privacy‐by‐design (e.g., fine‐grained controls such as Immuta or equivalent).
- Advanced analytics/AI (incl. GenAI where appropriate) for decision support, recommendations, or productivity.
Director, Sales Analytics in London employer: 慨正橡扯
As a leading player in the financial services sector, our company offers an exceptional work environment for the Director of Sales Analytics role, where innovation meets collaboration. With a strong emphasis on hands-on analytics and AI/ML, employees are empowered to drive measurable commercial impact while enjoying a culture that prioritises professional growth and development. Located in a dynamic market, we provide access to cutting-edge technology and a supportive network of senior stakeholders, ensuring that your contributions are recognised and valued.
StudySmarter Expert Advice🤫
We think this is how you could land Director, Sales Analytics in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like 慨正橡扯!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Director, Sales Analytics at 慨正橡扯.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like 慨正橡扯.
✨Apply Directly through Our Website
When you find a suitable opening like Director, Sales Analytics at 慨正橡扯, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Director, Sales Analytics in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at 慨正橡扯, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at 慨正橡扯. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at 慨正橡扯
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at 慨正橡扯!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.