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 enabling Arm’s engineering teams to design products using the power of machine learning and statistics? Are you passionate about working in a team that thrives on creativity, innovation, and diversity?

Arm is using Machine Learning and Data Science techniques to empower our engineers to make data-driven decisions, and to build automated workflows that enable our engineers to deliver more complex products. Based in the Machine Learning for Verification (ML4V) team in Arm’s Productivity Engineering group, this role will enable you to directly impact Arm’s production engineering processes, and to help improve future generations of Arm-based technology used by 70% of the world’s population.

As a senior data scientist in ML4V, you will be responsible for ensuring that our machine learning pipelines are correctly integrated into engineering workflows and performing well for the company. This means that you will ensure our data science pipelines are implemented to a high-quality engineering standard and perform in a robust way on modern cloud architecture. You will assess and improve their performance and impact on the engineering workflows. You will explore new opportunities and develop new data science solutions that show potential for meaningful impact when put into production. You will be helping to create an ecosystem for data science solutions to grow and flourish automatically and continuously. This collection of activities and responsibilities will enable you to build your skills across the entire data science pipeline from early exploration to deployment.

Responsibilities:

• Invent and develop data science solutions from inception to production
• Implement the pipeline of devised data science solutions with clean code and rigorous tests in the production environment
• Design and implement continuous performance assessment of the deployed solutions, driving impact improvement by working with cross-functional teams (including data science, ml engineering, ml compute, and hardware engineering teams)
• Support the scalability and sustainability of deployed solutions
• Discuss and explain results to technical and non-technical stakeholders
• Help to improve the deployment process of data science products by working closely with compute engineers, data engineers and stakeholders.

Required Skills and Experience:

• Demonstrable experience of coding with Python, using libraries such as Pandas/ Numpy/ scikit-learn/ matplotlib, etc.
• Demonstrable knowledge of data analysis, statistics and machine learning (e.g. dimension reduction, clustering hypothesis testing, regression models, gradient boosting algorithms, etc,)
• Bachelor’s Degree in Computer Science, Applied Mathematics, Bioinfomatics, Applied Physics, Computer Engineering or equivalent.
• Demonstrable experience in data science/ analytics, or machine learning engineering
• Great teammate, willing to collaborate with and support others in the team
• Excellent interpersonal, written, and verbal communication skills
• Passion for new skills and knowledge
• Embrace diversity and inclusion in workplace, open to different ideas and cultures
• Strong analytical and problem-solving skills

Nice To Have Skills and Experience:

• A master or PhD degree in relevant fields such as statistics, computer science, bioinformatics, applied mathematics, computer engineering, applied physics etc
• Experience working on deployment of data science pipelines
• Experience with DevOps and CI/CD tooling – eg Git/ Jenkins/ Automated testing tools/ Continuous Deployment, A/B Testing.
• Knowledge or experience in fields of reinforcement learning or deep learning, such as Bidirectional Encoder Representations from Transformers (BERT), LambdaNetworks and ResNet as well as tools such as Tensorflow, Keras and Pytorch