Junior Data Scientist

Lumanity applies incisive thinking and decisive action to cut through complex situations and deliver transformative outcomes to accelerate and optimise access to medical advances. With deep experience in medical, commercial, and regulatory affairs, Lumanity transforms data and information into real-world insights and evidence that powers successful commercialization and empowers patients, providers, payers, and regulators to take timely and decisive action.

We are currently looking for a Junior Data Scientist to join our busy and exciting Analytics team. As a Junior Data Scientist, you will be a curious data scientist, keen to develop and grow your commercial career in this field.

Purpose of Role:

• As a contributing member of Lumanity’s analytics team, you will be a technically strong, curious junior data scientist, keen to develop and grow your commercial career in this field. The team fulfils the technical expert role throughout pharmaceutical market research project pipelines, from proposal, design, analysis, to presentations. We work under the principles of technical rigour, reproducibility, and scalability.

Core Job Responsibilities

• To assist with research design (e.g. experiment/survey), data pre-processing, and statistical analysis/modelling/deliverables of multiple data sources with a data scientist mentality (“automate & re-use”)
• To participate first-hand as we shape, implement, and deliver quality research to help our clients answer complex questions to grow their business
• You will need excellent communication skills, as you will work with multiple internal research & other analytics teams

Software Stack

• R (basic proficiency essential)
• MS Office (basic proficiency in Excel essential)
• SPSS (basic proficiency desirable)
• SQL, Python (not essential

Algorithmic Stack

• Segmentation & Discriminant analysis & tools (desirable)
• Predictive modelling (e.g. logistic regression) (desirable)
• Choice/Allocation based models (desirable)
• Decision/Regression based trees (desirable)
• Key Driver analysis methods (desirable)
• Multivariate analysis (desirable)
• Machine learning/AI methods (desirable)
• Experimental design (desirable)
• Bayesian methods (not essential)
• Time series analytics (not essential)
• Text analytics (not essential)

Useful Stack

• Structured data wrangling (desirable)
• Data science best practices (e.g. version control, scripts & libraries, reproducibility) (desirable)
• BI & web-app development (not essential)
• Unstructured data wrangling (not essential)
• Pharmaceutical and/or healthcare experience (not essential)

Requirements

Education

• Strong degree (2:1) in any analytics related field (e.g. statistics, mathematics, physics, engineering) subject and/or professional qualification

Non-essential experience

• Desirable experience in industries/sectors that use survey data heavily (e.g. market research, opinion polls, psychological/medical research), though not essential.

Benefits

• Competitive salary
• Early finish Friday
• Hybrid working
• Pension plan
• Private Health Care