Data Scientist

Data Scientist

Manchester Full-Time 28800 - 48000 £ / year (est.) No home office possible
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Gazprom Energy

At a Glance

  • Tasks: Join our Portfolio Modelling team to develop insights and forecasts in the energy sector.
  • Company: SEFE Energy, a dynamic B2B energy supplier with a focus on innovation.
  • Benefits: Competitive salary, bonus potential, hybrid working, and extensive benefits package.
  • Why this job: Make an impact in the energy industry while growing your data science skills.
  • Qualifications: Proficiency in Python, SQL, and machine learning; analytical experience required.
  • Other info: Inclusive culture that values diversity and supports career development.

The predicted salary is between 28800 - 48000 £ per year.

Are you an experienced Data Scientist looking to join an organisation committed to placing data and technology at the heart of their business model? As a B2B energy supplier, SEFE Energy supplies thousands of businesses across the UK, France, and Netherlands. To remain competitive, we must be agile, constantly adapting to the ever-changing energy world, driven by forces of decarbonisation, competition, digitalisation, and shifting customer expectations. Our Always Reaching for Better strategy equips us to respond to changes and advancements, and quickly seize opportunities to grow and develop.

We are looking for someone to join our Portfolio Modelling team in Manchester or London. Working with key stakeholders, you will help develop tailored insight into demand and portfolio forecasts across Gas, Power & Emissions. This is a fixed term contract for up to 12 months to cover maternity leave.

What you will do?

  • Work closely with your immediate colleagues whilst building effective working partnerships across Portfolio Management, Sales, Risk, and Finance to ensure we maintain rigour and accuracy around our data modelling and produce industry-leading forecasts.
  • Develop, deploy, and maintain industry-leading modelling solutions and deliver analytical insights to support wider business success.
  • Deal with the discovery of new structured & unstructured data sources from internal systems, industry APIs/web scraping/file flows, Counterparty news sources & market participant data sets.
  • Collaborate with risk management in the development of new products and solutions to minimise portfolio risk and exposure.
  • Ensure a stable & automated operating environment, with strong backup & benchmarking processes, for data analytics, visualisation, quality assurance, report content monitoring, and issue resolutions.
  • Liaise across our stakeholders to ensure tier one insight into portfolio EBITDA performance, customer metrics, price & fundamental influences, and external portfolio impacts.
  • Build strong collaborative relationships with key stakeholders to ensure the desk, department, business forecasts, and insights are industry-leading.
  • Input in R&D for concept & prototype development for data mining & data-gathering techniques leading into ML/AI design and forecast data visualisation.

What you’ll bring to the role?

You will bring proven experience in an analytical role demonstrating the ability to work at pace whilst maintaining a high degree of accuracy. Self-motivated with strong organisational skills, you will have effective communication skills (both written and verbal) with the ability to position your message appropriately for the audience.

You will also demonstrate the following:

  • High level proficiency in Python, SQL, and Machine learning techniques.
  • Advanced analytical competencies.
  • Experience using data visualisation tools.
  • Knowledge of forecasting techniques.
  • Exposure to production engineering technologies such as Docker.
  • Proven experience in data science across finance, trading, or energy industry.
  • Experienced in the delivery of time series forecasting and analysis (desirable).

Our offer to you

In return, we offer a competitive starting salary supported by a comprehensive, and broad-reaching benefits package which includes:

  • Bonus earning potential.
  • Non-contributory pension.
  • 25 days holiday plus bank holidays.
  • Buy/sell holidays.
  • Life assurance.
  • Allowance for medical and dental insurance.
  • Range of optional flexible benefits.

Based from our offices in either Manchester or London, you can benefit from hybrid working offering the flexibility to spend some of your working week at home. We are committed to supporting your career growth with opportunities to develop both your knowledge and experience through a blended approach to learning.

Who are we?

We are part of the SEFE Group – led by SEFE Securing Energy for Europe GmbH in Berlin – which employs approximately 1,500 employees. The 350 people working in SEFE Energy are friendly and positive – you can approach anyone for help and your ideas are always welcome. We’re committed to our REACH principles – Results, Expertise, Action, Challenge, Have courage – but above all else, we care for each other’s welfare and aspirations and above all offer support as your career develops.

Our focus for 2022 – 2025 is strategic, profitable growth and strengthening our foundations, primarily by placing data and technology at the heart of our business model. We’re looking for people who are passionate about where we’re going and will help us thrive long into the future.

We’re committed to creating an inclusive environment that embraces diversity and fosters the development of knowledge, skills, and experience, so all our people can thrive and prosper in their careers with us. We are a place where you can be yourself and make your mark because whatever your role, you’ll find an open, welcoming atmosphere that empowers you, encourages fresh thinking, and recognises your contribution.

Data Scientist employer: Gazprom Energy

SEFE Energy is an exceptional employer that prioritises data and technology, fostering a collaborative and inclusive work culture in either Manchester or London. With a competitive salary and comprehensive benefits package, including hybrid working options and a strong focus on employee growth, we empower our team to thrive while contributing to the energy sector's evolution. Join us to be part of a friendly and supportive environment where your ideas are valued and your career aspirations are nurtured.
Gazprom Energy

Contact Detail:

Gazprom Energy Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Scientist

✨Tip Number 1

Network like a pro! Reach out to current employees at SEFE Energy on LinkedIn or attend industry events. Building connections can give you insider info and might just land you an interview.

✨Tip Number 2

Prepare for the interview by brushing up on your Python, SQL, and machine learning skills. Be ready to discuss how you've used these in past roles, especially in the energy sector.

✨Tip Number 3

Show your passion for data and technology! During interviews, share examples of how you've leveraged data insights to drive business decisions. This aligns perfectly with SEFE's commitment to placing data at the heart of their model.

✨Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team.

We think you need these skills to ace Data Scientist

Python
SQL
Machine Learning Techniques
Data Visualisation Tools
Forecasting Techniques
Data Mining
Analytical Skills
Communication Skills
Organisational Skills
Collaboration
Time Series Forecasting
Production Engineering Technologies
Stakeholder Management
Problem-Solving Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV speaks directly to the Data Scientist role. Highlight your experience with Python, SQL, and any relevant machine learning techniques. We want to see how your skills align with our needs!

Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data and how you can contribute to our Always Reaching for Better strategy. Let us know why you're excited about joining SEFE Energy.

Showcase Your Analytical Skills: In your application, don’t forget to mention specific projects or experiences where you've demonstrated your analytical prowess. We love seeing real examples of how you've tackled challenges in the past!

Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and keep track of it. Plus, it shows you’re keen on joining our team!

How to prepare for a job interview at Gazprom Energy

✨Know Your Data Inside Out

As a Data Scientist, you'll be expected to have a solid grasp of data modelling and forecasting techniques. Brush up on your Python and SQL skills, and be ready to discuss specific projects where you've successfully implemented these tools. Prepare examples that showcase your analytical competencies and how they relate to the energy sector.

✨Understand the Business Context

Familiarise yourself with SEFE Energy's business model and the challenges facing the energy industry today. Be prepared to discuss how your skills can help the company adapt to changes in decarbonisation, digitalisation, and customer expectations. Showing that you understand the bigger picture will impress your interviewers.

✨Prepare for Technical Questions

Expect technical questions related to machine learning techniques and data visualisation tools. Review common forecasting methods and be ready to explain how you've applied them in past roles. Practising coding problems or case studies relevant to the role can also give you an edge.

✨Showcase Your Collaboration Skills

Since the role involves liaising with various stakeholders, highlight your experience in building collaborative relationships. Prepare examples of how you've worked effectively with teams across different departments, particularly in finance, risk management, or sales. This will demonstrate your ability to communicate complex data insights clearly and effectively.

Data Scientist
Gazprom Energy
Location: Manchester
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