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- Tasks: Lead innovative data science projects to optimise decision-making in the utilities sector.
- Company: Join a dynamic team focused on sustainable solutions in asset management and energy operations.
- Benefits: Enjoy remote work options, a supportive environment, and opportunities for career advancement.
- Why this job: Make a real impact while working on exciting projects that contribute to a sustainable future.
- Qualifications: Degree in a quantitative field with 2+ years of data science experience; strong skills in SQL, R, and Python.
- Other info: Inclusive workplace valuing diversity and offering support for all applicants.
The predicted salary is between 30000 - 42000 £ per year.
Duration: 6 Months
Location: Warwick / Remote
Are you ready to make a significant impact in the utilities sector? Join our client's dynamic Data Science team as a Data Scientist, where your expertise will drive data-driven solutions that enhance decision-making for asset management and energy system operations. Dive into exciting projects that support regulatory commitments and contribute to our ongoing business-as-usual initiatives!
What You'll Do:
- Optimising Decision-Making: Develop and deliver data-driven solutions for gas transmission system operations and asset management.
- Collaborative Engagement: Work closely with internal stakeholders to identify opportunities and refine data-driven strategies.
- Data Management: Identify, collect, clean, and process relevant datasets, ensuring seamless handover to Data Engineers.
- Model Development: Create and deploy predictive and prescriptive models using Azure ML Studio and Azure DevOps.
- Effective Communication: Present findings clearly through visualisation and reporting, including interactive dashboards and web applications using Power BI, R Shiny, or Python Flask.
- MLOps Maintenance: Maintain and enhance MLOps pipelines, focusing on model robustness and performance.
- Project Tracking: Manage code and project tracking using Git and Azure DevOps Boards, aligned with Scaled Agile Framework (SAFe) practices.
- Cross-Functional Collaboration: Partner with data engineers, system operators, and other business users to ensure seamless integration of solutions.
What You Bring:
- Hands-On Experience: Proven experience in data science and machine learning model deployment, preferably with Azure ML Studio.
- MLOps Proficiency: Strong understanding of pipeline management and model versioning.
- Data Manipulation Skills: Expertise in data extraction, transformation, and reshaping using SQL, R/Tidyverse, and Python/Pandas.
- Visualisation Expertise: Experience with data visualisation tools and frameworks such as Power BI, R Shiny, and Python Flask.
- Agile Methodology: Familiarity with Git and Azure DevOps for version control and agile task management.
- Statistical Acumen: Solid understanding of statistical methods and machine learning algorithms.
- Effective Communication: Ability to convey complex technical concepts to both technical and non-technical audiences.
- Problem-Solving Attitude: Strong proactive approach to identifying and resolving challenges.
Preferred Qualifications:
- Experience in the energy or utilities sector, particularly in asset management optimisation and supply-demand forecasting.
- Understanding of SAFe practices, including PI Planning and Retrospectives.
- Experience working in hybrid team structures, collaborating with contractors and external partners.
Qualifications:
A degree in a quantitative field (STEM Bachelor's/Master's) with strong foundations in Linear Algebra, Calculus, and Statistics, plus 2+ years as a Data Scientist. Alternatively, substantial industry experience combined with recognised certifications in Data Science demonstrating hands-on implementation.
Why Join Us?
This is more than just a job; it's a chance to contribute to a sustainable future while advancing your career in a supportive and innovative environment. If you're passionate about data science and eager to tackle meaningful challenges, we'd love to hear from you!
Apply Now! Take the next step in your career and help shape the future of the utilities industry with us. Your journey starts here!
Pontoon is an employment consultancy. We put expertise, energy, and enthusiasm into improving everyone's chance of being part of the workplace. We respect and appreciate people of all ethnicities, generations, religious beliefs, sexual orientations, gender identities, and more. We do this by showcasing their talents, skills, and unique experience in an inclusive environment that helps them thrive. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you.
Data Scientist - 01229 employer: Pontoon
Contact Detail:
Pontoon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - 01229
✨Tip Number 1
Familiarise yourself with Azure ML Studio and Azure DevOps, as these are crucial tools for the role. Consider working on personal projects or contributing to open-source projects that utilise these platforms to showcase your hands-on experience.
✨Tip Number 2
Brush up on your data manipulation skills using SQL, R/Tidyverse, and Python/Pandas. You might want to create a portfolio of projects that demonstrate your ability to extract, transform, and visualise data effectively.
✨Tip Number 3
Engage with the data science community, especially those focused on utilities and energy sectors. Networking can provide insights into industry trends and may lead to valuable connections that could help you in the application process.
✨Tip Number 4
Prepare to discuss your problem-solving approach during interviews. Think of specific examples where you've tackled challenges in data science projects, particularly those involving model deployment and MLOps, to demonstrate your proactive attitude.
We think you need these skills to ace Data Scientist - 01229
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly with Azure ML Studio and MLOps. Use specific examples that demonstrate your skills in data manipulation, model development, and collaboration.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and the utilities sector. Mention how your background aligns with the job requirements and provide examples of past projects that showcase your problem-solving abilities and effective communication skills.
Showcase Technical Skills: Clearly outline your technical skills related to SQL, R/Tidyverse, Python/Pandas, and data visualisation tools like Power BI. Consider including a portfolio or links to projects that demonstrate your expertise in these areas.
Prepare for Interviews: If selected for an interview, be ready to discuss your previous work in detail. Prepare to explain your approach to data-driven decision-making and how you have collaborated with cross-functional teams in the past.
How to prepare for a job interview at Pontoon
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with data science and machine learning model deployment, especially using Azure ML Studio. Bring examples of projects where you've successfully implemented predictive models and how they impacted decision-making.
✨Demonstrate Collaborative Spirit
Highlight your ability to work closely with internal stakeholders. Share specific instances where you identified opportunities for data-driven strategies and how you engaged with others to refine these approaches.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. Be ready to present your findings using visualisation tools like Power BI or R Shiny, and ensure you can articulate the insights derived from your data analysis.
✨Emphasise Problem-Solving Skills
Prepare to discuss challenges you've faced in previous roles and how you approached solving them. A proactive problem-solving attitude is crucial, so share examples that demonstrate your analytical thinking and adaptability.
