Data Scientist II

Data Scientist II - NAV01TI

Company: Worley

Primary Location: IND-MM-Navi Mumbai

Other Locations: IND-KR-Bangalore, IND-MM-Mumbai, IND-MM-Pune, IND-TN-Chennai, IND-GJ-Vadodara, IND-AP-Hyderabad, IND-WB-Kolkata

Job: Digital Platforms & Data Science

Schedule: Full-time

Employment Type: Employee

Job Level: Experienced

Job Posting: Jul 10, 2024

Unposting Date: Sep 9, 2024

Reporting Manager Title: Senior Manager

:

Building on our past. Ready for the future

Worley is a global professional services company of energy, chemicals and resources experts. We partner with customers to deliver projects and create value over the life of their assets. Were bridging two worlds, moving towards more sustainable energy sources, while helping to provide the energy, chemicals and resources needed now.

At Worley, our Digital team collaborates closely with the business to deliver efficient, technology-enabled sustainable solutions, that will be transformational for Worley. This team, aptly named Worley Digital, is currently seeking talented individuals who would be working on a wide range of latest technologies, including solutions based on Automation, Generative AI.

What drives us at Worley Digital  Its our shared passion for pushing the boundaries of technological innovation, embracing best practices, and propelling Worley to the forefront of industry advancements. If youre naturally curious, open-minded, and a self-motivated learner - one whos ready to invest time and effort to stay future-ready - then Worley could be your ideal workplace.

Position Title (Global): Sr ML Engineer

Industry Specific Experience:
 Minimum 4- Maximum 7 year experience as Sr ML Engineer on AI and ML projects.

Major Accountabilities of Position : a Sr ML engineer must have

Priority

What - How  Why

% of total job

1

Development of the Generative AI Solutions with LLM (OpenAI/Anthropic/NVIDIA)

Research and implement new machine learning algorithms and techniques. Keep up to date with advances in machine learning and artificial intelligence. Identify opportunities to apply machine learning to improve existing products or create new ones.

30%

2

Develop data pipelines to automate the data processing and model training process.

Verifying data quality, and/or ensuring it via data cleaning, Data labelling to smaller dataset if required. Ensure data quality and integrity.

Collaborate with data engineers and other team members to manage and maintain data infrastructure. Supervising the data acquisition process if more data is needed.

Finding available datasets online that could be used for training.

Defining the preprocessing or feature engineering to be done on a given dataset.

20%

3

Defining data augmentation pipelines for unstructured data like Documents, Engineering drawings etc.

Build new network architecture in CNN/LSTM/RCNN or Develop wrapper for pre-trained models. Conduct feasibility of transfer learning fitment for given problem.

Training models and tuning their hyperparameters.

20%

4

Deploy machine learning models into production systems. Monitor and maintain the performance of deployed models. Collaborate with software engineers to ensure smooth integration and deployment. Conduct research on new emerging tools and technique for NLP, Image Processing and bring their application to complex unsolved business issues

20%

5

Provide mentorship and guidance to junior machine learning engineers and data scientists. Collaborate with cross-functional teams to develop and deliver machine learning solutions. Analyze the errors of the model and utilize available tools/technique to overcome them. Deploy models to production.

10%

Knowledge / Experience / Competencies Required

IT Skills & Experience (Priority wise):

1. Proven experience as a ML Engineer  AI/ML not data scientist or data analyst

2. Ability to write robust code in Python for machine learning solutions.

3. Experience in AI solution development with external SaaS

4. Experience in the AI/ML components like Azure ML studio, Jupyter Hub, TensorFlow & Sci-Kit Learn

5. Hands-on knowledge of API frameworks.

6. Proficiency in using version control systems like Git to track and manage code changes.

7. Experience using the cognitive APIs machine learning studios on cloud.

8. Up to speed on NLP (Summarization, Translation models, Named Entity Recognition),

9. Hands-on knowledge of image processing with deep learning ( CNN,RNN,LSTM,GAN)

10. Understanding of complete AI/ML project life cycle

11. Understanding of data structures, data modelling and software architecture

12. Good understanding of containerization and experience working with Docker.

People Skills:
 Ability to communicate clearly and concisely and a flexible mindset to handle a quickly changing culture.
 Ability to work independently and as part of a team.
 Being open to new ideas, embracing change, and adapting to evolving technologies and methodologies are crucial for staying relevant and effective in the rapidly changing field of machine learning.
 Cooperative mindset, flexibility, and the ability to work effectively in a team.
 Professional and open communication to all internal and external interfaces.
 Accurately report to management in a timely and effective manner.

Other Skills:
 Outstanding analytical and problem-solving skills

Education  Qualifications, Accreditation, Training:
 Masters in Information Technology / Big Data/Data Science/AI/Computer Science

Moving forward together


We want our people to be energized and empowered to drive sustainable impact. So, our focus is on a values-inspired culture that unlocks brilliance through belonging, connection and innovation.

And we're not just talking about it; we're doing it. We're reskilling our people, leveraging transferable skills, and supporting the transition of our workforce to become experts in today's low carbon energy infrastructure and technology.

Whatever your ambition, theres a path for you here. And theres no barrier to your potential career success. Join us to broaden your horizons, explore diverse opportunities, and be part of delivering sustainable change.,