Senior Data Science Consultant

Life as a Senior Data Science Consultant at Blend

We are looking for someone who is ready for the next step in their career and is excited by the idea of solving problems and designing solutions using cutting edge tools. However, they also need to be aware of the practicalities of making a difference in the real world – whilst we love innovative advanced solutions, we also believe that sometimes a simple solution can have the most impact. 

Our Senior Data Science Consultant is someone who feels the most comfortable around messy data, solving problems and answering questions. We place a high value on the ability to communicate and translate complex analytical thinking into non-technical and commercially oriented concepts, and experience working on difficult projects and/or with demanding stakeholders is always appreciated.

Reporting into the Data Science and BI team, and working closely with the Data Engineering team, this role will be responsible for driving high delivery standards and innovation in the company. Typically, this involves using data analytics and machine learning to conduct in-depth analysis which uncovers actionable insights and then reporting the findings back to stakeholders in a clear and relevant manner.

As the Data Science and BI team grows, mentoring junior analysts/data scientists and leading project teams will also form part of day-to-day functions.

What can you expect from the role?

• Preparing and presenting compelling analysis findings to clients and senior stakeholders.
• Use a variety of analytical tools and methods to deliver regular reports and deep dive strategic analytics.
• Own tasks end-to-end and manage the process and team of analysts.
• Contributing to proposal submissions and business development initiatives under the direction of the Leadership team.
• Supporting the development of the data science team within Blend.
• Support in the road-mapping of analytical projects.

What you need to have?

• Proven experience as a Data Scientist, with a strong portfolio of data science projects; ability to demonstrate how to perform data cleaning, QC and exploratory analysis to discover key insights.
• Commercial experience using predictive modelling (supervised and unsupervised) and proficiency in programming languages like Python and R or similar; solid understanding of database technologies and SQL.
• Strong knowledge and experience using predictive modelling (supervised and unsupervised) machine learning, data mining, and statistical modelling in a commercial setting.
• Experience in leading and delivering projects, managing and owning the data science solution (or parts of it) and team of analysts in a non-academic setting.
• Excellent communication and collaboration skills; ability to work effectively in a fast-paced, dynamic environment.

Nice to have

• Experience more complex applications of ML such as NLP, computer vision or optimization is advantageous.
• Ability to work and process large amounts of data/experience working with cloud environments.
• Experience and working knowledge of relevant sectors (e.g. manufacturing, energy, public sector, automotive and utilities industries) is desired but not essential. 
• Experience with proposal submissions and business development initiatives under the direction of the Leadership team.
• Experience in designing data science solutions from concept through to evaluation and monitoring models in production.
• Experience in managing teams or supporting team development.

A diverse workforce is a strong workforce
To deliver growth at Blend and for our clients, we have a responsibility and unique opportunity to positively impact the workforce. Diversity has played a critical role in our history, our growth, and continues to have a profound impact on our success. We are determined to have equality in the workplace, within our team and as an extension of our clients’ team.

This is not the work of the moment, this requires continued learning and purposeful actions. We are investing resources to understand and improve the sourcing, selection and retention of the talent we hire.