Data Scientist (Consultant)

Qualifications Required

Undergraduate/Masters degree in STEM or other numerate subjects. Plus 3 or more years relevant working experience.

OR

PhD in a relevant field (Machine Learning, Industrial Analytics etc.) plus one year commercial experience

Skills and Experience

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 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, 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.

Providing an agile culture and challenging work opportunities results in a positive work environment.  Our people enjoy competitive compensation packages and a fun, personal, collaborative and safe working environment.  We value equal employment opportunity and are committed to promoting fairness, equality and diversity.

Our policy is to conduct background checks for all candidates who accept an offer of employment with us.