Machine Learning Engineer

4 weeks ago

Mumbai, Maharashtra, India Collinson Full time
About the Role

We are seeking a highly skilled Machine Learning Engineer to join our team at Collinson. As a key member of our data science team, you will play a critical role in driving the development of cloud-based machine learning pipelines for data-driven products and services.

Your responsibilities will include collecting data from various business units, leveraging a centralized data platform to productionize analytics and machine learning workflows, and providing analytical expertise across the Collinson group.

You will work closely with our data platform team to integrate with the ML platform and support the growth and development of the team's ML skillset.

Key Responsibilities:

  • Drive the development of machine learning pipelines for data-driven products and services
  • Contribute to architecture and technical decisions to create machine learning workflows and pipelines in cloud (e.g. AWS)
  • Collaborate with data scientists and engineers to deploy new machine learning and deep learning models into complex and mission-critical production systems
  • Select the right tool(s)/services(s) for the job and make it work in production
  • Promote a culture of self-serve data analytics by minimizing technical barriers to data access and understanding
  • Stay current with the latest research and technology and communicate your knowledge throughout the enterprise

Day-to-Day Activities

As a Machine Learning Engineer at Collinson, you will be responsible for working on all stages of projects (planning, development, quality control, production), designing, building, and maintaining our strategic platform and tooling, producing machine learning models, including supervised and unsupervised methods, rapidly prototyping proof-of-concept ideas, converting proof-of-concept projects to enterprise solutions, producing reports and presentations to communicate findings to stakeholders, and investigating and understanding emerging trends in data-related approaches.

Team Working

You will be an active member of the data & analytics team, contributing to team dynamics, ways of working, and assisting with improvement opportunities. You will also be an active member of internal Data and Analytics communities, providing regular and accurate reports of progress to technical leads and the Project lead where required, building strong relationships with stakeholders, maintaining strong technical awareness and familiarity with new and upcoming technologies around Data Integration and Business Intelligence Analysis, and staying abreast of the industry and participating in external communities to keep up to date and offer the most informed position when defining or consulting on solution design.

Knowledge, Skills, and Experience Required

You will have knowledge of common data science techniques, including data preparation, exploration, and visualization, knowledge of data mining techniques in one or more areas of statistical modeling, time series, text mining, optimization, and information retrieval, ability to produce workflows using classification, clustering, regression, and dimensionality reduction, ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data-driven solutions to problems in new domains, knowledge of industry best practice in deploying data science solutions, strong knowledge of the AWS Well Architected Framework(s), and a data science and engineering background.

Core Competencies

You will have data science and engineering skills in PySpark, PySpark ML, Python, Hive, Postgres, Sklearn, machine learning skills in collaborative filtering, NLP, TFIDF, decision trees, regression, clustering, data science and analytical background, interacting with technical and non-technical stakeholders, machine learning and exploratory data analysis, and experience with various messaging systems, such as Kafka.

Desired Technical Skills

You will have experience using Kubernetes or similar orchestration systems, in-depth understanding of relational database systems, experience with various messaging systems, such as Kafka, experience with distributed computing frameworks, such as Hadoop Spark, deep learning and artificial intelligence skills, cloud providers experience, and visualization and UI skills.

Experience

You will have commercial analytical experience, a degree in STEM or equivalent, data modeling skills, strong awareness of the appropriate application of denormalization, aggregation, warehousing, and data lakes, experience building and deploying APIs, experience with AWS, Azure, in development and production, experience with Big Data Ecosystem (Hadoop), experience maintaining production-grade workflows, experience of the full Software Development Lifecycle, utilizing both Agile and Waterfall Project Delivery methods, and consultative experience in data science engineering or machine learning.

Person Specification

You will be a self-motivator with a desire to learn new skills and embrace new technologies in a constantly changing technology landscape, able to thrive in a fast-moving environment, able to show initiative, innovation, and work independently when required, able to work at pace and tackle project challenges in a collegiate, collaborative way, goal and outcome-oriented, thorough and attention to detail, good communication skills, ability to bridge communications between technical and business-focused groups, comfortable working with people at all levels in an organization, and willing to take on a variety of roles and responsibilities.

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