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Following up on my recent Machine Learning Predictive APIs and Apps: conference report post, I thought it might be nice to continue with the Machine Learning theme. So this week I have gathered five interesting ML opportunities.

1. Senior Machine Learning Scientist, Deep Learning

Amazon – Seattle, WA

Job Description:

We are looking for a Machine Learning Scientist to build our next generation of recommender systems. We experiment rapidly using the latest machine learning techniques such as Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Matrix Factorization. We work with Machine Learning experts across Amazon to deliver the best possible recommendations, leveraging Amazon’s vast computing resources (AWS) and data. We deal with large amounts of training data, rapid prototyping, offline/online testing, and high-performance requirements.

This role will require working with Sr. Managers, Principal Engineers, and Program Managers. You should be excited to dive deep, iterate rapidly, and have a desire to learn and try new things. You will work with a team of scientist and engineers who are passionate about machine learning and using AI to make a sizable impact on our customers. You will dive deep into multiple Deep Learning architectures, review papers, and implement solutions to improve our current recommendations and come up with new, novel alternatives.

Roles and Responsibilities:

Research and implement novel machine learning and computational models to solve problems that matter to our customers.

Be efficient in aligning research direction to business requirement and make the right judgment on research project prioritization.

Mentor and develop a high performing team of Machine Learning Engineers and Research Scientists.

Stay informed on the latest machine learning trends in general, including recommender systems and deep learning.

Understand business requirements and customer needs, and map to a scientific problem.

Own end-to-end experimentation, from conception/research, offline testing and live A/B testing.

Doctoral Degree in Computer Science, Electrical Engineering or related field or Master’s Degree with at least 3 years of professional experience.

Solid research track record with peer-reviewed publications in top academic conferences and journals in the related areas

Experience of at least one modern programming language such as Java, C/C++, or Python

5+ years of hands-on experience in predictive modeling and analysis

1+ years of professional experience in software development

Strong Computer Science fundamentals in data structures, algorithm design, problem-solving, and complexity analysis

1+ years of experience applying neural networks/deep learning to solve real-world problems

Experience working with Spark, Hadoop and AWS (EMR, EC2, S3, etc

Solid coding practices including good design documentation, unit testing, peer code reviews

Experience building high-performance computational software

Experience working with real-world noisy data

Solid understanding of A/B testing

Experience designing statistical tools targeted at non-statistical users

2. Business Intelligence Analyst, Advanced Analytics

Google – Mountain View, CA, USA

Job Description:

As part of the Finance Business Intelligence team, you will use data to inform business and product decisions across the company. Using your technical skills, business acumen and creativity, you will build tools to automate reporting and generate insight that will allow clients to quickly and accurately see how our key business products and processes are performing. Previous experience managing financial systems projects, with emphasis on providing business intelligence and data-driven insight through reporting, will have equipped you well for this role. You’ll be involved in projects from inception to delivery, ensuring that your reporting delivers high-quality and relevant data to intelligently grow our business. You will also have extensive knowledge of key financial systems, such as Oracle and Hyperion, and experience working with a range of other business intelligence tools and platforms.

Roles and Responsibilities:

Use knowledge of predictive analytics, statistics and modeling techniques to develop and improve the sophistication of Business Intelligence solutions.

Own and drive agenda to upskill colleagues in the Finance Business Intelligence team on predictive methodologies.

Work closely with senior finance management and their teams to understand their information needs, ensuring that Business Intelligence (BI) strategy and agreed solutions are an excellent fit to their evolving needs.

Manage, own and deliver multiple BI work streams, both on an ongoing and ad-hoc basis.

Work with Engineering partners to help shape and drive the development of Google’s BI infrastructure including Data Warehousing, reporting and analytics platforms.

3. Data Scientist

Sportsbet – Melbourne, Australia

Job Description:

We’re looking to take our mathematical modeling to the next level and are looking for a new Data Scientist to join our growing team. Our Data Scientists are responsible for improving the performance of the business through predictive analytics and the development of mathematical models. As a key member of the Data Science team, the role will involve close collaboration with stakeholders across the business.

Roles and Responsibilities:

Identify potential uses of mathematics and computer science to improve the performance of the business.

Work closely with key stakeholders to deliver optimization solutions such as predictive models to maximize the ROI of online marketing activities.

Develop mathematical models such as financial prediction models based on an understanding of the underlying structure of the business and the market.

Develop classification and regression models to build an understanding of the customer to drive optimal customer interactions.

Develop a strong knowledge of sports and racing betting by predicting the outcome of events.

Design software solutions in accordance with software engineering best principles such as TDD to deliver high-quality products.

Set up and monitor infrastructure using technologies such as Linux, Python, and Amazon Redshift.

4. Data Scientist – Algorithms, Numerical Computing, Machine Learning, Big Data, Cloud, Python, Scala, R

Elsevier – London, United Kingdom

Job Description:

We are expanding a new Data Science team within our analytics department. Your role will involve working with huge amounts of data, developing algorithms, implementing machine learning techniques, dissecting results and making predictions from time series’ and social networks. You should expect to research and apply new techniques and methods as applicable, continuously striving to improve tools and practices applied to each stage of the analytics lifecycle. Though the role will be based in London, you will be working with colleagues in Amsterdam as well as London.

Roles and Responsibilities:

1. Develop and implement analysis strategies / numerical algorithms to answer specific business and research questions

Define analysis/algorithm goals working with product managers and rest of the team.

Develop numerical code (in Python using Numpy/Pandas/Scikit-learn, Scala or R) to run on a single node machine or distributed cluster (using Spark/HDFS).

Report on and explain analysis/algorithm outcomes. Use reporting templates and explain results in a non-technical way.

2. Implement & maintain data analysis pipeline on distributed cloud-based analytics platforms

Implement code for processing ‘big data’ using parallel distributed cluster architecture

Ensure that the right data is fed into any analysis/algorithm and is suitably cleaned (and limitations of subsequent cleaning documented)

Maintain code and outputs in shared directories (using Git or alternative)

3. Assist in reporting on analysis and research outputs to wider business and research communities as required

Engage in discussions with product managers/ wider team to extract true meaning of analysis

Obtain and analyze data, creating tables, graphs and visualizations to assist in demonstrating the key findings of the analysis/algorithm

Help produce presentation material to describe key outcomes

5. Azure Architect

Job Description:

This is a unique opportunity for a highly experienced Infrastructure Engineer to take a lead role in the delivery of enterprise-scale managed services including Business Intelligence, Enterprise Performance Management, Data Science and Big Data. In this key position, you will be responsible for the design, implementation and ongoing management of Microsoft Azure cloud-based infrastructure for enterprise-scale Business Intelligence and Big Data services.

Roles and Responsibilities: