At a Glance
- Tasks: Lead data-driven marketing projects and develop innovative solutions for business challenges.
- Company: Join Google’s dynamic team, tackling real-world problems with cutting-edge analytics.
- Benefits: Competitive salary, career growth, and the chance to work with industry leaders.
- Other info: Foster talent development in a collaborative environment focused on innovation.
- Why this job: Make a global impact by transforming data into actionable insights for marketing strategies.
- Qualifications: Master's degree in a quantitative field and 7 years of analytics experience required.
The predicted salary is between 63000 - 77000 £ per year.
hackajob is partnering directly with Google to hire for this role. Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
As a Data Science Manager in the Marketing Media Lab team, you will lead projects, translating business problems into investigative solutions and you will guide your team to implement data science solutions, improve data, develop metrics, and build models for business insights. You will also foster knowledge sharing and develop your team's talent. You will play a strategic and technical role in driving all things media, marketing, analytics, and partnering with internal teams to evaluate strategic initiatives. Using first-party and third-party data sources, you will create innovative solutions to demonstrate the effectiveness of Google's media investment and the industry's toughest issues, at a global scale.
Minimum qualifications:
- Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
- 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Preferred qualifications:
- 2 years of experience managing an Analytics or Data Science team, including prioritisation, roadmapping, coaching and performance management.
- Experiences with experimental design and supervised/unsupervised ML approaches for regression and classification tasks.
- Experience of root cause analysis to ensure that problems are solved at both a tactical and strategic level.
- Experience delivering marketing analytics e.g., Marketing Mix Modeling, geo experiments, meta-analysis, audience segmentation and propensity modeling.
- Understanding of Bayesian approaches and modeling frameworks.
- Proven ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership with cross functional stakeholders.
Responsibilities:
- Provide support in media strategy, measurement and optimization that require expertise in advanced analytics work, with special focus on marketing analytics methods and data science.
- Partner with internal teams in advanced analytics work including experimentation, measurement and modeling.
- Identify patterns and behaviors that are effective predictors of performance and critical drivers for a successful media plan.
- Deliver customer-centric, data-driven approach, based on a people-based marketing strategy to build, segment, and test audiences for best business results.
- Partner with internal teams to scope, build and deliver strategic initiatives driving all things marketing data, with a strong focus on digital marketing data pipelines.
- Lead and develop the team, taking ownership of team roadmapping, initiative prioritization, individual coaching, and ongoing performance management.
Data Science Manager, Marketing employer: Hackajob Ltd
Hackajob Ltd is an exceptional employer located in the vibrant town of Wallingford, offering a dynamic work culture that fosters collaboration and innovation. Employees benefit from comprehensive training and growth opportunities within the logistics sector, while also enjoying a supportive environment that values their contributions to optimising robotic deployments. With a focus on employee well-being and a commitment to maintaining a balanced work-life dynamic, Hackajob Ltd stands out as a rewarding place to build a meaningful career.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Manager, Marketing
✨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 Hackajob Ltd!
✨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 Data Science Manager, Marketing at Hackajob Ltd.
✨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 Hackajob Ltd.
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We think you need these skills to ace Data Science Manager, Marketing
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 Hackajob Ltd, 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 Hackajob Ltd. 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 Hackajob Ltd
✨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 Hackajob Ltd!
✨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.
