At a Glance
- Tasks: Join our Global AI & Data Science team to develop impactful data science models.
- Company: Haleon, a purpose-driven consumer health company with trusted brands.
- Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative environment with mentorship opportunities and a focus on responsible AI.
- Why this job: Make a real difference in everyday health using cutting-edge AI and data science.
- Qualifications: MS or PhD in Data Science or related field with strong machine learning skills.
The predicted salary is between 63000 - 77000 £ per year.
Welcome to Haleon. We’re a purpose-driven, world-class consumer company putting everyday health in the hands of millions. In just three years since our launch, we’ve grown, evolved and are now entering an exciting new chapter – one filled with bold ambitions and enormous opportunity. Our trusted portfolio of brands – including Sensodyne®, Panadol®, Advil®, Voltaren®, Theraflu®, Otrivin®, and Centrum® – lead in resilient and growing categories. What sets us apart is our unique blend of deep human understanding and trusted science.
Now it’s time to fully realise the full potential of our business and our people. We do this through our Win as One strategy. It puts our purpose – to deliver better everyday health with humanity – at the heart of everything we do. It unites us, inspires us, and challenges us to be better every day, driven by our agile, performance-focused culture.
About the role: This is an exciting opportunity to join our Global AI & Data Science team. AI, Data Science and Machine learning are critical elements of our digital strategy. We are investing to build best in class data science capabilities, so our AI solutions deliver impact and meet our Responsible AI requirement.
Key Responsibilities
- Participate in creating, evolving, and developing data science models for Marketing, Commercial and Digital.
- Work closely with product owners, data engineers and machine learning engineers to deliver high quality data science powered solutions to interesting problems.
- Help prepare datasets to train and validate machine learning models.
- Define and implement metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance.
- Support the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning.
- Manage the whole lifecycle of our machine learning models, including monitoring, gathering data for retraining, and redeployments.
- Leverage third-party and syndicated data to provide value-added learnings on trade promotions, pricing, distribution, and digital shelving to key stakeholders and specifically for joint business operations.
- Drive marketing automation, e.g. audience targeting and profiling, content production, digital marketing campaigns optimization.
- Conceive and implement statistical models and Multi-Variate Tests to measure the impact of business decisions and market disruptions to surface empirical insights.
Teamwork
- Contribute to a highly collaborative team with a culture of openness and ownership.
- Work closely with key stakeholders and influence them on business objectives.
- Enable collaboration by contributing to the development of our AI foundations and reusable assets for Forecasting, Optimization, Segmentation, Attribution Models and Experimentation.
- Perform code reviews and ensure exceptional code quality.
- Manage & mentor junior data scientists & apprentices.
- Build a culture of responsible AI, good governance, and ethics.
Qualifications & Skills
- MS or PhD degree in Data Science, Computer science, applied mathematics, statistics, or another relevant discipline with a strong foundation in modelling and computer science.
- Extensive industry experience with developing machine learning models and creating software pipelines to build and make predictions with those models.
- Strong understanding of machine learning approaches and algorithms.
- Deep understanding of Statistical/Probabilistic programming and Linear Algebra.
- Be an expert in (Python, R, SQL) programming for Data Science and Time Series analysis.
- Have in depth understanding of statistical modelling / ML techniques for time series forecasting (ARIMA, ETS, Prophet, Time Series pattern detection, and ML methods).
- Strong experience with Causal inference, Intervention analysis, Counterfactuals Estimation, Optimization and Scenarios simulation.
- Solid experience with Probabilistic Programming and Bayesian Methods.
- Experience using machine learning frameworks such as scikit-learn, Pymc, TensorFlow, PyTorch, Databricks ML, Keras etc.
- Experience with ML at scale.
- Experience coordinating projects across diverse teams.
- Proven attention to detail, critical thinking, and the ability to work both independently and collaboratively within a cross-functional team.
- Strong communication skills including to non-technical audiences.
Equal Opportunities: Haleon are committed to mobilising our purpose in a way that represents the diverse consumers and communities who rely on our brands every day. It guides us in creating an inclusive culture, where different backgrounds and views are valued and respected – all in support of understanding and best serving the needs of our consumers and unleashing the full potential of our people.
Adjustment or Accommodations Request: If you require a reasonable adjustment or accommodation or other assistance to apply for a job at Haleon at any stage of the application process, please let your recruiter know by providing them with a description of specific adjustments you are requesting.
Note to candidates: The Haleon recruitment team will contact you using a Haleon email account (@haleon.com). If you are not sure whether the email you received is from Haleon, please get in touch.
Senior Data Scientist employer: GSK
GSK is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation in the heart of Stevenage. With a strong commitment to employee growth, you will have access to extensive development opportunities while working on groundbreaking medicine projects. The hybrid work model and future relocation to Cambridge provide a unique advantage, ensuring a vibrant environment for both personal and professional advancement.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist
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We think you need these skills to ace Senior Data Scientist
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 GSK, 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 GSK. 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 GSK
✨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 GSK!
✨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.