Data Scientist (Consultant)

Energy Resourcing

Energy Resourcing are currently recruiting for a Data Scientist (Consultant) to join our client’s London project delivery team permanently.

The successful candidate will join a Unconventional Industrial Solutions team on a hybrid/remote basis with limited requirements to travel.

Machine Learning

• Skilled at building predictive models to solve a wide range of problem types, choosing the right approach(es) to maximise performance. Seeks constantly to broaden the repertoire of ML approaches used. Able to work in a variety of machine learning applications and coding libraries.
• Can demonstrate hands-on experience in at least four of the following machine learning applications: Regression, Classification, Clustering, Dimensionality Reduction, Deep Learning (AI), Reinforcement Learning, and Optimisation.
• Au fair with current machine learning tools and platforms such as Python, IBM, Knime, Github, R, Spark, Weka, Amazon ML, Azure ML, etc.

Analytical Knowledge

• Design an analytical project incorporating the right approaches and datasets to solve a given problem.
• Mine data to understand its quality and distribution, informing model choice and transformations needed.
• Perform statistical tests on model output to assess performance and ensure the validity of conclusions.

Applied Analysis and Insight

• Draw on domain expertise to choose the most appropriate analytical approach.
• Work with customers and subject matter experts throughout a project to ensure data is interpreted correctly and solutions are viable.
• Present models to non-technical audiences in compelling business-oriented terms.
• Present data in a visually compelling and elegant way making it easy to interpret and draw conclusions.
• Experience in analysis of IOT/Sensor Data to solve problems in an industrial setting.

Technical

• Write code to access and process diverse data types from a range of on-prem and cloud sources.
• Familiar with cloud computing and big data technologies (Azure, AWS, Hadoop, Spark, Snowflake, etc).
• Comfortable working on data platforms, such as Snowflake or Databricks, to manipulate data to engineer model features.
• Familiarity with the technologies used to validate, monitor and deploy ML models (Tensorflow, ML Flow, AWS Studio, Docker, Kubernetes, etc).

Softer Skills

• Spend time with customers to fully understand the challenges and the nuances of their organisation and data.
• Develop generalised approaches to solving problems in models and code.
• Bring data and analytics to life through storytelling and excellent written and verbal skills.
• Be comfortable working in Agile project-management frameworks.

• Undergraduate/Masters degree in STEM or other numerate subjects, plus relevant working experience OR PhD in a relevant field (Machine Learning, Industrial Analytics, etc.) plus commercial experience.
• Experience working in a similar role, within the Engineering, Industrial or Manufacturing industry.