Data Engineer/ ML Engineer

About Us

We know that people are our "greatest asset". Our staff’s professionalism, innovation, teamwork and dedication to excellence have helped us become one of the world’s leading technology companies. It is these qualities that are vital to our continued success. As a Ness employee you will be working on products and platforms for some of the most innovative software companies in the world. The opportunity to evolve your expertise by using new cutting edge technologies will expand your horizons and create an exciting work environment. You’ll also gain enormous knowledge working alongside other highly skilled professionals that will help accelerate your career progression. At Ness we treat our values of rigor, innovation and partnership with the highest priority and they are placed at the very core of our business — to guide us through our daily operations and interactions with our customers. We offer our employees exciting and challenging projects across a diverse range of industries, as well as the opportunity to collaborate with a group of forward thinking, capable partners around the globe.

About Client

Its primary areas of business are financial information and analytics. It is the parent company of S&P Global Ratings, S&P Global Market Intelligence, and S&P Global Platts, CRISIL, and is the majority owner of the S&P Dow Jones Indices joint venture.

Roles and Responsibility

As a ML Engineer in the S&P Global Data Science team, you will work on multiple data science projects in collaboration with internal and external project owners on the product, commercial, and data team. You will be responsible for providing machine learning engineers support, create data pipeline for modeling, scale models, develop APIs to help move machine learning models in productions. You will collaborate with the data scientists and production-oriented software engineers

You will be part of a rapidly growing organization, joining the team of highly motivated and professional Data Scientists and Machine Learning Engineers within S & P Global Market Intelligence division. Market Intelligence provides financial and industry data, research, news and analytics to investment professionals, government agencies, corporations, and universities worldwide. We integrate news, comprehensive market and sector-specific data and analytics into a variety of tools to help clients track performance, generate alpha, identify investment ideas, understand competitive and industry dynamics, perform valuations, and assess credit risk.

We are looking for candidates from a diverse pool of graduate & postgraduate institutions that are passionate to build, scale and deploy Machine Learning Models that provide timely and essential intelligence to our disparate array of customers across the globe.

What’s in it for you:

We provide a highly inclusive work environment where in you can bring your whole self to work to assist S&P Global in achieving its mission of being one of the leading providers of the highest quality risk evaluations and analytical information to the world’s financial markets. As an integral part of our team, you will be working on cutting edge state-of-the-art technology stack. In this role, you will work on multiple data science projects in collaboration with internal and external project owners on the product, commercial, and data team. You will be responsible for providing machine learning engineers support, create data pipeline for modeling, scale models, develop APIs to help move machine learning models in productions. You will collaborate with the data scientists and production-oriented software engineers

Requirements

- Construct machine learning lifecycle management including data collection, normalization, and standardization within a data pipeline construction

- Develop AutoML infrastructure for model selection and hyperparameter tuning

- Create applications and interface to present the output of ML models

- Experiment, develop and productionize high quality machine learning services and platforms to make huge technology and business impact.

- Develop hosting platform for machine learning models.

- Create pipelines to query and retrieve and update data for existing applications to keep them updated

- Supervise the scaling and management of the machine learning modeling ecosystem

- Work alongside data scientists and product owners to improve aspects of their lines of business through machine learning.

What We’re Looking For:

- Possess excellent verbal & written communication skills

- Expertise in application, data, and infrastructure architecture disciplines

- Advanced knowledge of architecture and design across all systems

- Proficiency in multiple machine learning programming languages including Python, PySpark, or Scala

- 3 + years of experience with big-data technologies such as Hadoop, Spark, SparkML, etc

- Able to understand various data structures and common methods in data transformation

- Knowledge of industry-wide technology trends and best practices

- Ability to work in large, collaborative teams to achieve organizational goals

- Passionate about building an innovative culture

- Familiarity with MLOps and ModelOps

- Docker, Kubernetes, AWS, Python

- Familiarity with or clear interest in learning about financial Markets.

Basic Qualifications:

- BS/BA degree in computer science or engineering

Benefits

• A flexible work environment with an opportunity to work remotely
• Modern and spacious office with a city view, fresh fruits, and other perks
• A successful and growing, multi-cultural company with a globally distributed team
• Full health insurance that covers sports, massage, physiotherapist, vaccination, etc.
• Continual professional and personal development through employer-paid trainnings and certifications e.g., AWS, English/Latvian language courses and much more
• Motivating referral policy and if you are lucky, you can get a Grand Prize
• Supplementary vacation days based on seniority level
• Mobile phone expenses coverage
• Car and Bicycle parking place
• And other benefits