AWS Data Scientist (Expression of Interest) - Melbourne

at  The Data Foundry

Company Description
We are a customer-obsessed, “one stop shop” for all things data-related. We are deliberately narrow in our focus areas but we go deep in each of them. We provide solutions, services and training in the data strategy, data governance, data security, data management, data classification, data wrangling, data lake, data analytics, data visualisation, artificial intelligence, machine learning and IoT areas. Our solutions and services help transform customer organisations by teaching them how to turn their data into insight!
We build on AWS, using the latest AWS services, best practices and reference architectures. We deliberately focus on large public sector customers that are data-heavy but insight-light – federal & state government departments, universities, public sector agencies, public health organisations, and public utilities.
We are an AWS Advanced Consulting Partner and an AWS Public Sector Partner, working towards our Data & Analytics and Government competencies. We are also a registered technology supplier to the Federal, New South Wales, Victorian and Western Australian governments and we have a Master Services Agreement in place with AWS Professional Services.
Job Description
As a AWS Data Scientist, you will play a key role designing and implementing data science infrastructure, machine learning models, algorithms, and statistical analyses to extract insights from large datasets in the cloud.
You will work closely with clients to understand their data needs and provide customised solutions using the latest AWS technologies. You will have considerable experience working on data-related solutions using AWS and will be comfortable working with technical resources including data analysts, data engineers and other data scientists, to enable customers to generate insight from their data.
You will relish the opportunity to innovate, evolve and test existing assumptions and design bold solutions. Your experience with large-scale data challenges and ability to create reliable, scalable cloud-based solutions, will see you thriving in this role!

Expectations:

• Work with clients to understand their data needs and identify opportunities for analytics and ML solutions.
• Enjoy honing your data-related analysis skills and developing new ones, so you can make strong contributions to solution discussions.
• Have a demonstrated ability to think strategically about solutions to business, product, and technical challenges.
• Build predictive models using machine learning techniques such as regression, classification, clustering, and time series analysis.
• Continuously monitor and improve the performance of data models and algorithms.
• Collaborate with data engineers to design and implement data pipelines and workflows.
• Be dynamic, creative, and willing to take on challenges that have the potential to make a big impact.
• Regularly take part in further education and training to help you hone and extend your data science and analytical skills.
• Relish a ground floor opportunity to work in a small, agile, friendly startup environment.
• An AWS Associate Solutions Architect or any ML specialty certification is a bonus.

Qualifications

Technical Requirements:

• Tertiary qualifications in computer science, data science, or a related field.
• At least 2 years of experience in data modelling, statistical analysis, and machine learning.
• Programming skills in one or more of the following languages: Python, Java, Scala, R, and SQL.
• Strong understanding of machine learning lifecycle such as Data labelling, EDA, Feature engineering, Feature retrieval, Error analysis, Model deployment and Monitoring.
• Experience with AWS technologies such as S3, Lambda, EMR, Glue, Redshift, and SageMaker.
• Experience with machine learning tools such as Scikit-learn, TensorFlow, PyTorch, and Hugging face to build and analyse models in different problem settings.
• Experience in working with different machine learning algorithms such as Logistic Regression, Decision Trees, KNN, SVM, PCA, Ensemble methods, Neural Networks.
• Knowledge of data visualisation tools such as Tableau, Power BI, or AWS QuickSight.
• Experience and understanding of container technology, especially Docker (Desirable).
• Experience in a consulting or client-facing role is a plus.

Additional Information

Please refer the Job description for details