Senior Data Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

Are you interested in the semiconductor industry and Arm’s growth trajectory within it? How about applying Data Science to modeling macroeconomic phenomenon? If you are passionate about machine learning, statistics, programming, are creative, innovative, and champion diversity, then this role is for you!

Arm is using Machine Learning and Data Science techniques to equip leadership with the tools they need to make lucrative strategic decisions derived from data. Our aim is to develop models that provide future insight whilst applying MLOps practices. As a data scientist within Insights, you will be responsible for ensuring that our machine learning pipelines are correctly integrated within AWS and will train, test and validate results using appropriate methodologies. This means that you will ensure our pipelines have a stable implementation for on-prem and cloud infrastructures, and you will assess and improve their performance alongside Software Engineers, Data Scientists and Analysts. You will have opportunity to utilize AWS services such as AWS Sagemaker, Redshift, RDS, ECR, Lambda and Cloudwatch in practice. You will explore new opportunities to develop new data science solutions that illustrate potential for a meaningful impact for Arm. Your primary focus will be improving revenue forecasting techniques and modeling macroeconomic behaviours, working with a plethora of individuals from a variety of disciplines and seniority. You will present results to senior leaders within Arm and will be required to explain complexity, simply.

Responsibilities:

• Take Data Science projects from inception to production
• Develop high quality Data Science pipelines using Python, which meet customer requirements
• Monitor and assess performance of deployed pipelines
• Discuss and explain results to technical and non-technical customers
• Exhibit creativity and a self-starter ethos to demonstrate the power and value of Data Science within Arm

Required Skills and Experience (Not all required for the correct candidate)

• University Degree in STEM subjectand/orproven experience as a Data Scientist
• Understanding of Statistics and relating python packages with a specialist interest in time-series forecasting (ARIMA, GARCH, State Space Models and Decomposition Techniques. Packages: ‘Prophet’ and ‘Statsmodels’)
• Strong project management and presentation skills
• Deep understanding of supervised and unsupervised machine learning problems and techniques e.g., regression, classification, and clustering
• Experienced in software development with Python, especially libraries such as scikit-learn, pandas and matplotlib etc.
• Great teamwork, willing to collaborate with and support others in the team. Has a passion for new skills, has excellent interpersonal, written, and verbal communication skills
• Embraces diversity and inclusion in workplace, open to different ideas and cultures

Nice To Have Skills and Experience:

• A Masters or PhD within relevant fields such as statistics, computer science, economics, applied mathematics, computer engineering
• Knowledge and passion for deep learning and applicability to business insight ( for example, LSTM’s, MLP’s, CNN’s, GAN’s and Transformers) . Some knowledge of NLP, graph theory and supervised / unsupervised clustering algorithms is useful. (Tensorflow, Keras and Pytorch)
• Experience with CI/CD within a Data Science context

Arm is committed to global talent acquisition, offering an attractive relocation package. With offices around the world, Arm is a diverse organisation of dedicated, creative and highly talented engineers. By enabling a dynamic, inclusive, meritocratic, and open workplace, where all our people can grow and succeed, we encourage our people to share their unrivaled contributions to Arm's success in the global marketplace.