Data Scientist

• Fix issues with plugins for our Python-based ETL pipelines
• Help with automation of standard workflow
• Deliver Python microservices for provisioning and managing cloud infrastructure
• Responsible for any refactoring of code
• Effectively manage challenges associated with handling large volumes of data working to tight deadlines
• Manage expectations with internal stakeholders and context-switch in a fast-paced environment
• Thrive in an environment that uses AWS and Elasticsearch extensively
• Keep abreast of technology and contribute to the engineering strategy
• Champion best development practices and provide mentorship to others

• First and foremost you are a Python developer, experienced with the Python Data stack
• You love and care about data
• Your code is an artistic manifest reflecting how elegant you are in what you do
• You feel sparks of joy when a new abstraction or pattern arises from your code
• You support the manifests DRY (Don’t Repeat Yourself) and KISS (Keep It Short and Simple)
• You are a continuous learner
• You have a natural willingness to automate tasks
• You have critical thinking and an eye for detail
• Excellent ability and experience of working to tight deadlines
• Sharp analytical and problem-solving skills
• Strong sense of ownership and accountability for your work and delivery
• Excellent written and oral communication skills
• Mature collaboration and mentoring abilities
• We are keen to know your digital footprint (community talks, blog posts, certifications, courses you have participated in or you are keen to, your personal projects as well as any kind of contributions to the open-source communities if any)

• Delivering complex software, ideally in a FinTech setting
• Experience with CI/CD tools such as Jenkins, CircleCI
• Experience with code versioning (git / mercurial / subversion)

• Deliver plugins for our Python-based ETL pipelines
• Deliver Python microservices for provisioning and managing cloud infrastructure
• Implement algorithms to analyse large data sets
• Draft design documents that translate requirements into code
• Effectively manage challenges associated with handling large volumes of data working to tight deadlines
• Manage expectations with internal stakeholders and context-switch in a fast-paced environment
• Thrive in an environment that uses AWS and Elasticsearch extensively
• Keep abreast of technology and contribute to the engineering strategy
• Champion best development practices and provide mentorship to others

• First and foremost you are a Python developer, experienced with the Python Data stack
• You love and care about data
• Your code is an artistic manifest reflecting how elegant you are in what you do
• You feel sparks of joy when a new abstraction or pattern arises from your code
• You support the manifests DRY (Don’t Repeat Yourself) and KISS (Keep It Short and Simple)
• You are a continuous learner
• You have a natural willingness to automate tasks
• You have critical thinking and an eye for detail
• Excellent ability and experience of working to tight deadlines
• Sharp analytical and problem-solving skills
• Strong sense of ownership and accountability for your work and delivery
• Excellent written and oral communication skills
• Mature collaboration and mentoring abilities
• We are keen to know your digital footprint (community talks, blog posts, certifications, courses you have participated in or you are keen to, your personal projects as well as any kind of contributions to the open-source communities if any)

• Delivering complex software, ideally in a FinTech setting
• Experience with CI/CD tools such as Jenkins, CircleCI
• Experience with code versioning (git / mercurial / subversion)

Job Description

We are looking for a highly capable machine learning engineer to optimize our deep learning systems. You will be evaluating existing deep learning (DL) processes, do hyperparameter tuning, performing statistical analysis (logging and evaluating model’s performance) to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities.

You will be working with technologies like AWS Sagemaker, TensorFlow JS, TensorFlow/ Keras/TensorBoard to create Deep Learning backends that powers our application.
To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in Deep Learning role. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software. To do this job successfully, you need exceptional skills in DL and programming.

Responsibilities

• Consulting with managers to determine and refine machine learning objectives.

• Designing deep learning systems and self-running artificial intelligence (AI) software to

  automate predictive models.

• Transforming data science prototypes and applying appropriate ML algorithms and

  tools.

• Carry out data engineering subtasks such as defining data requirements, collecting,

  labeling, inspecting, cleaning, augmenting, and moving data.

• Carry out modeling subtasks such as training deep learning models, defining

  evaluation metrics, searching hyperparameters, and reading research papers.

• Carry out deployment subtasks such as converting prototyped code into production

  code, working in-depth with AWS services to set up cloud environment for training,

  improving response times and saving bandwidth.

• Ensuring that algorithms generate robust and accurate results.

• Running tests, performing analysis, and interpreting test results.

• Documenting machine learning processes.

• Keeping abreast of developments in machine learning.
  
  Requirements

• Proven experience as a Machine Learning Engineer or similar role.

• Should have indepth knowledge of AWS Sagemaker and related services (like S3).

• Extensive knowledge of ML frameworks, libraries, algorithms, data structures, data

  modeling, software architecture, and math & statistics.

• Ability to write robust code in Python & Javascript (TensorFlow JS).

• Experience with Git and Github.

• Superb analytical and problem-solving abilities.

• Excellent troubleshooting skills.

• Good project management skills.

• Great communication and collaboration skills.

• Excellent time management and organizational abilities.

• Bachelor's degree in computer science, data science, mathematics, or a related field;

  Master’s degree is a plus.