Job Description

About L.E.K. Consulting

L.E.K. Consulting is a global management consulting firm that uses deep industry expertise and rigorous analysis to help business leaders achieve practical results with real impact.

We are uncompromising in our approach to helping clients consistently make better decisions, deliver improved business performance and generate greater shareholder returns.

The firm advises and supports global companies that are leaders in their industries including the largest private and public sector organizations, private equity firms and emerging entrepreneurial businesses.

Founded more than 35 years ago, L.E.K. employs more than 1,800 professionals across the Americas, Asia-Pacific and Europe.

Data scientist

Requisition ID : Location :

BRUXELLES, BE,

About US (GEMS)

ENGIE Global Energy Management & Sales (GEMS) provides energy supply solutions and risk management services to support its clients through their decarbonization journey, while optimizing ENGIE’s assets and contributing to value creation.

ENGIE is a global reference in low-carbon energy and services with a leading energy management business, piloted by its entity "Global Energy Management & Sales" who built its savoir-faire managing the Group’s large and diverse asset portfolio over 20+ years.

3, employees around the world develop our solutions, through +20 international business platforms. We cover the full energy mix : renewable and thermal power, natural gas & LNG, biomass, environmental products.

Our experts provide tailor made solutions based on a wide range of savoir-faire in energy management with a strong focus on decarbonation and decentralization.

Our +, clients span the entire value chain : producers, asset developers, financial players, utilities, distributors and industrials.

Our global reach and strong local presence enable us to offer these diverse clients tailor-made services and respond to rapid changes in mature or emerging markets alike.

Our 4 expertise :

• Asset management
• Energy transition services
• Energy supply & global commodities
• Risk management & market access

At GEMS we encourage breakthrough results, team spirit, curiosity and innovation while preserving the right work / life balance for you.

Organization

Position open within the Quantitative Research and Modeling Expertise Center (EC QRM) and BP Short term Power as a Service.

EC QRM provides advanced quantitative expertise to all Business Platforms (BP) of GEMS.

YOUR contribution

Context

The role of the Data Scientist is to provide analysis, models and tools to the optimization and trading desks, using data science tools and state-of-the art quantitative models.

The Team Manager of Power & Emissions QRM's team will be your direct manager.

Role

The data scientist will be focused on the activities related to the CWE power markets. He will leverage large amount of data using machine learning and state-of-the art quantitative models to deliver analysis and tools that have a concrete impact on the business, including :

• Prediction of relevant power market signals
• Asset optimization
• Trading algorithm

Key missions

The daily responsibilities include :

• Contribute to the digitalization and data-driven trading decision of GEMS
• Develop, improve and support our models and tools
• Leverage complex data to provide market insight
• Be in direct contact with traders and optimizers desks to understand their business needs and propose solutions
• Be in direct contact with Quants and Market Analysts, to exchange about models, new ideas, in order to leverage on the knowledge from peers
• Be in direct contact with the IS team to be aligned on coding best practices and IS architectures

Travels

Punctually for conferences

About YOU

Hard skills

• Strong mathematical skills, expert in statistics, machine learning and optimization,
• In-depth understanding of the energy business and power markets,
• Demonstrated coding skills (Python) in order to develop autonomously prototypes & models,
• Ability to explain and convey messages about complex issues,
• Programming languages GIT, Microsoft suite,
• Experience with data science techniques

Soft skills

• Analyzing, Practical thinking, Entrepreneurship,
• Planning, developing others,
• Conceptual thinking, working together.

Education and professional background

• University degree in Statistics, Mathematics, Physics, Engineering, Computer Sciences,
• Experience in short term power markets is a plus

Languages

Fluent in English

If you meet these requirements, then you are the talent we are looking for. Do not waste time!

Apply by attaching your updated CV, regardless your gender.

ENGIE Global Energy Management & Sales is committed to create a gender-neutral environment that unlocks the potential of everyone and provide equal employment opportunities for all individuals.

All our positions are open to people with disabilities, please let your recruiter know if you need reasonable accommodations to be able to participate in the recruitment process, they will be happy to assist you.

About ENGIE

Our group is a global reference in low-carbon energy and services. Our purpose ( raison d’être ) is to act to accelerate the transition towards a carbon-neutral world, through reduced energy consumption and more environmentally-friendly solutions, reconciling economic performance with a positive impact on people and the planet.

We rely on our key businesses (gas, renewable energy, services) to offer competitive solutions to our customers. With our , employees, our customers, partners and stakeholders, we are a community of Imaginative Builders, committed every day to more harmonious progress.

Description

Where you fit in

We play an important role by developing, deploying, and operating Information and Digital Technologies which enable Shell to produce more and cleaner energy for the world.

Shell’s Information and Digital Technologies organisation applies technical, commercial, and emerging digital technologies skills to help Shell industrial assets competitively optimise energy production while reducing emissions intensity.

We partner with our business to replicate technologies across our business portfolios.

What’s the role?

As a full stack data scientist, you will get to apply your knowledge in statistics, time series analysis, and dynamical systems, work with the latest machine learning models, and build predictive models for energy consumption, energy generation, and energy price, and make an impact by helping Energy Marketing business in Shell Energy to make better, safer, more sustainable decisions which yields to cleaner and more sustainable world.

You will work with a team of data engineers and scientists who use data and apply cutting statistical machine learning models to build forecasting models for different energy markets.

The entire Data team works collaboratively and is a strong partner for teams across the company. You will get to meet and learn from diverse and talented colleagues.

Accountabilities

• Analyze energy time series and summarize the statistical properties of energy signals
• Build predictive models and forecast signals for day-ahead and real-time markets
• Evaluate the performance and compare the results with existing models
• Deploy the best model and document the result of this research

What we need from you?

• Must have legal authorization to work in the US on a full-time basis for anyone other than current employer
• Minimum of three (3) years’ experience of deploying machine learning models and frameworks in production
• Bachelor’s Degree is preferred
• Proficiency developing end-to-end machine learning training and inference pipelines at scale to be able to forecast hundreds of thousands of meters daily over a variable day horizon under both recursive and direct modelling approaches
• Proficiency with Python or R, SQL and familiarity with working in big data environments
• Minimum of five (5) years’ experience with :
• Experiences in both Supervised and Unsupervised machine learning models (Regressions, Gradient Boosted methods, SVMs, Random Forests, Clustering)
• Hyperparameter tuning of machine learning models
• Familiar with python packages such as Pandas, SkLearn, Numpy etc
• Time Series Analysis (ARIMA, SARIMAX, MA)
• Deep learning (CNN, RNN, LSTM) and framework library (e.g., Keras, TensorFlow, PyTorch) and Graph Neural Networks
• End to end machine learning lifecycle experience including feature engineering, model building, model versioning, evaluation and hypothesis testing.
• Minimum of three (3) years’ experience with Cloud computing platforms such as AWS, Azure (preferably AWS)
• Deployment of AWS Sagemaker models and pipelines and serverless architecture
• Containerization and orchestration technologies such as Docker and Kubernetes.
• Standard concepts and technologies used in CI / CD build and deployment pipelines.
• Experience in distributed and parallel computing frameworks such as Spark / Pyspark / Multiprocessing / Multithreading
• Working knowledge of the power and renewable energy markets

COMPANY DESCRIPTION

Shell is a global group of energy and petrochemicals companies with over 90,000 employees in more than 70 countries and territories.

In the US, we have operated for over a century and are a major oil and gas producer onshore and in the Gulf of Mexico, a recognized innovator in exploration and production technology, and a leading manufacturer and marketer of fuels, natural gas and petrochemicals.

We deliver energy responsibly; operate safely with respect to our neighbours and work to minimize our environmental impact.

We are in search of remarkable people who will thrive in a diverse and inclusive work environment to deliver exciting projects locally and globally.

People who are passionate about exploring new frontiers. Innovators and pioneers. People with the drive to help shape our future.

Because remarkable people achieve remarkable things.

An innovative place to work

There’s never been a more exciting time to work at Shell. Everyone here is helping solve one of the biggest challenges facing the world today : bringing the benefits of energy to everyone on the planet, whilst managing the risks of climate change.

Join us and you’ll add your talent and imagination to a business with the power to shape the future whether by investing in renewables, exploring new ways to store energy or developing technology that helps the world to use energy more efficiently.

An inclusive place to work

To power progress together, we need to attract and develop the brightest minds and make sure every voice is heard. Here are just some of the ways we’re nurturing an inclusive environment one where you can express your ideas, extend your skills and reach your potentials.

We’re creating a space where people with disabilities can excel through transparent recruitment process, workplace adjustments and ongoing support in their roles.

Feel free to let us know about your circumstances when you apply, and we’ll take it from there

• We’re closing the gender gap whether that’s through action on equal pay or by enabling more women to reach senior roles in engineering and technology.
• We’re striving to be a pioneer of an inclusive and diverse workplace, promoting equality for employees regardless of sexual orientation or gender identity.
• We consider ourselves a flexible employer and want to support you finding the right balance. We encourage you to discuss this with us in your application

A rewarding place to work

Combine our creative, collaborative environment and global operations with an impressive range of benefits and joining Shell becomes an inspired career choice.

We’re huge advocates for career development. We’ll encourage you to try new roles and experience new settings. By pushing people to reach their potential, we frequently help them find skills they never knew they had, or make career moves they never thought possible.

Description

Position at Tokio Marine HCC

The need to anticipate and preempt potential markets and products has given rise to a new team : The Enhanced Product Innovation Collaboration or EPIC .

This team is looking for a Senior Data Scientist to help drive innovation.

Key Responsibilities

• Deliver start-to-finish on projects leveraging a large spectrum of data
• Design, build, and validate models using modeling techniques using advanced AI and Deep Learning solutions
• Work with key business leaders, underwriters, actuaries, and other stakeholder to receive data, requirements, deliverable format, etc.
• Lead cross-functional project teams
• Develop a high-level understanding of innovative data science tools and techniques
• Lead the establishment and promotion of best practices
• Build collaborative relationships across the organization

Education

• Bachelor’s Degree in quantitative discipline; statistics, data science, computer science, mathematics, physics, etc.
• Preference to having proven work experience in NLP, Deep Learning, or AI

Experience

• Relevant professional experience in a Data Scientist role
• Significant leadership or senior experience including mentoring and coaching junior teammates.
• Strong experience with analytical modeling tools -
• R or Python
• Predictive modeling
• Machine learning
• Experimental design
• Deep learning related technologies
• Proven experience defining and delivering on initially vague or informal projects or ideas from decision makers with competing objectives
• Demonstrated leadership competencies
• Excellent written and verbal communication
• Outstanding coaching skills in a business context and as it applies to team and project management

Data Scientist will be responsible for developing and implementing analytic solutions, working with vendors on software improvements, and training our team members on how to use the software and data.

The Data Scientist should have experience in data analysis, data visualization, and data management, with a focus on customer responsiveness and continuous improvement.

Key Responsibilities : Collect and analyze data from various sources within the manufacturing plant and precast projects, such as production data, quality control data, project progress, sales and estimating, and customer feedback.

Use TITAN to store and organize data, and to create reports and dashboards that provide insights into the performance of the plant and project progress.

Develop and maintain data visualization tools, such as charts and graphs, to help the plant's management team and project managers understand the data and identify trends and patterns.

Implement analytics solutions to improve the efficiency and productivity of the manufacturing plant while ensuring customer responsiveness and project visibility.

Work with vendors to ensure that the analytics solutions meet the needs of the plant and that projects are delivered on time and within budget.

Collaborate with other departments to identify and collect data that can be used to improve plant operations and customer responsiveness.

Monitor and maintain the analytics solutions to ensure they are functioning properly, and that customer responsiveness is maintained.

Create and maintain documentation related to the analytics solutions and Titan management. Work with vendors to ensure that the TITAN system is up-to-date and meeting the needs of the business, and to identify and implement new features or updates as necessary.

Train and support plant staff and office staff to effectively use the TITAN system to improve performance, including data analysis, data visualization, and data management, with an emphasis on customer responsiveness and project visibility.

Continuously improve the data analytics process, including the identification of new data sources, the development of new metrics, and the creation of more advanced visualization tools.

Support the decision-making process by providing data-driven insights and recommendations to management. Key performance indicators (KPIs) That may be used to measure the performance of Data Scientist : Reports generation : The number of reports generated and delivered to management on a regular basis.

Training completion rate : The percentage of team members who complete the training on how to use the software.Solution adoption rate : The percentage of team members who are actively using the analytics solutions.

Data accuracy : The percentage of data that is accurate and free of errors.Customer satisfaction : The level of satisfaction of the customers with the analytics solutions and the level of responsiveness.

Project completion rate : The percentage of projects that are completed on time and within budget.Continuous improvement : The level of effort and success in continuously improving the analytics solutions and Titan system to meet the changing needs of the business.

Data visualization : The percentage of important data that is represented visually in the ERM system, such as through charts and graphs.

Vendor management : The ability to effectively manage vendors to ensure the system is up to date, and new features are implemented as necessary.