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- Tasks: Lead data science projects, develop predictive models, and communicate insights to drive business strategy.
- Company: Join a cutting-edge tech company at the forefront of AI and data science innovation.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Be part of a dynamic team pushing the boundaries of AI while making impactful business decisions.
- Qualifications: Expertise in Python, machine learning, and strong stakeholder management skills required.
- Other info: Ideal for those passionate about data science and eager to stay ahead in AI advancements.
The predicted salary is between 43200 - 72000 £ per year.
Expert knowledge of statistics, machine learning, programming, data modelling, simulation, and advanced mathematics to recognise patterns, identify opportunities, pose business questions, and make valuable discoveries leading to better business decision making.
A proven track record of leading data science projects and teams, as well as a strong background in AI research and applied machine learning.
Expertise in key data science technologies and techniques, such as Python, Git, AWS, AWS Sagemaker, PyTorch, TensorFlow, Jax, Numpy, Scikit-learn, Time-series forecasting, Classification, Regression, Large-language models, and Experiment Design.
Strong stakeholder management skills and the ability to communicate complex ideas to a diverse audience.
A passion for data science and a commitment to staying abreast of the latest developments in AI research and a drive to continuously push the boundaries of what’s possible.
Job Responsibilities
- Uses a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms.
- Develops and tests hypotheses, analyses and interprets the results of product experiments.
- Communicates data-driven insights and delivers action plans that steer business strategy and decision-making for business segments.
- Works with client teams to translate prototypes into new products, services, and features and provides guidelines for large-scale implementations.
- Provides input and guidance on data visualisation techniques and opportunities.
Senior Data Scientist employer: GlobalLogic
Contact Detail:
GlobalLogic Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network with professionals in the data science field, especially those who have experience with the technologies mentioned in the job description. Attend industry meetups, webinars, or conferences to connect with potential colleagues and learn about the latest trends.
✨Tip Number 2
Showcase your leadership skills by discussing any previous projects where you led a team or initiative. Be prepared to share specific examples of how you managed stakeholders and communicated complex ideas effectively.
✨Tip Number 3
Stay updated on the latest advancements in AI and machine learning. Follow relevant blogs, podcasts, and research papers to ensure you can discuss current trends and innovations during interviews.
✨Tip Number 4
Prepare to demonstrate your technical skills through practical assessments or case studies. Familiarise yourself with the tools listed in the job description, such as Python and TensorFlow, and be ready to solve real-world problems using these technologies.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your expertise in statistics, machine learning, and programming. Include specific projects where you've led data science initiatives and mention the technologies you've used, such as Python, AWS, and TensorFlow.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and your commitment to staying updated with AI research. Discuss how your experience aligns with the job responsibilities and how you can contribute to the company's success.
Showcase Your Projects: If possible, include links to your portfolio or GitHub repository where you have showcased relevant projects. Highlight any predictive models or algorithms you've developed and the impact they had on business decisions.
Prepare for Technical Questions: Anticipate technical questions related to data modelling, machine learning techniques, and stakeholder management. Be ready to discuss your approach to problem-solving and how you communicate complex ideas to diverse audiences.
How to prepare for a job interview at GlobalLogic
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with key data science technologies like Python, AWS, and machine learning frameworks. Highlight specific projects where you successfully applied these skills, as this will demonstrate your technical proficiency.
✨Demonstrate Leadership Experience
Since the role requires leading data science projects and teams, share examples of how you've managed teams or projects in the past. Discuss your approach to stakeholder management and how you communicated complex ideas effectively.
✨Prepare for Problem-Solving Questions
Expect to tackle hypothetical scenarios or case studies during the interview. Practice articulating your thought process when designing predictive models or analysing data, as this will showcase your analytical skills and creativity.
✨Stay Updated on AI Trends
Show your passion for data science by discussing recent developments in AI research. Mention any relevant articles, papers, or conferences you've engaged with, as this demonstrates your commitment to continuous learning and innovation in the field.
