Data Scientist

Gazprom Energy; Manchester; Hybrid; GBP 40,000 - 60,000; Full time

Job summary

A leading energy supplier based in Manchester seeks an experienced Data Scientist for a fixed-term contract to cover maternity leave. You'll develop data modeling solutions, ensuring rigorous data accuracy and delivering strategic insights while collaborating across teams in a flexible, supportive environment.

Benefits

Bonus earning potential

Non-contributory pension

Buy/sell holidays

Life assurance

Medical and dental insurance allowance

Flexible benefits options

Qualifications

• Proven experience in an analytical role with high accuracy.
• Effective communication skills appropriate for varied audiences.
• Experience in finance, trading, or energy industry data science.

Responsibilities

• Develop and maintain industry-leading modeling solutions.
• Collaborate with stakeholders for accurate data modeling.
• Input into R&D for data mining and ML/AI design.

Skills

Python

SQL

Machine Learning

Data Visualization

Analytical Competencies

Tools

Docker

Job description

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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.

Want to join us on our journey?

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?

In the role of Data Scientist you will 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.

You will also

• 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 back up & benchmarking processes, for data analytics, visualization, 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
• 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.