Atkins Hiring for Lead Data Scientist at Gurgaon, Haryana, India Full Time

Job Description

As one of the world’s leading consultancies operating in the built and natural environment, we offer unparalleled opportunities for talented individuals in search of a rewarding career both in India and around the world. Atkins India is committed to design excellence in the delivery of first-class solutions which combine innovation, imagination, and best practice. Atkins is a member of SNC Lavalin Organization. Founded in 1911, SNC-Lavalin is a global, fully integrated professional services and project management company and a major player in the ownership of infrastructure. The combined entity of Atkins and SNC-Lavalin has created one of the largest global engineering and project management consultancies with approximately 50,000 employees and operating across 50 countries.
This role is for a Lead Data Scientist to join to join our Analytics and Artificial Intelligence team. We create state of art machine learning models to help business deliver high value, smart and market differentiating engineering products and services. The focus of our team is not providing insight for executives to make decisions, rather working on innovative algorithms and models that make intelligent, automated, decisions in real time, billions of times a day. To achieve that we collaborate with the engineering, sales, commercial and technology teams
You’ll dive into cutting edge machine learning models, experiment and apply new ones, and apply analytics at scale to impact the business.
Use the latest cloud and data technologies to train and deploy machine learning models at scale. If you can prove your approaches are good, they’ll be quickly deployed to production.
You’re passionate about asking and answering questions in large datasets, and you are able to communicate that passion. You have a keen desire to solve problems, and live to find patterns and insights within structured and unstructured data. You propose analytics strategies and solutions that challenge and expand the thinking of everyone around you. You’re looking for a role with diverse learning opportunities, growing and having fun while at it. You’re expected to keep abreast of the latest data science industry developments and coach the team on them.
Be enthusiastic in collaborating, developing relationships within the company, and finding new business applications of data science. Key Deliverables/Responsibilities

• Use data analysis techniques to deliver quick working prototypes to prove hypothesis by building statistical models using a range of tools including R, Python, and Spark
• Understand data requirements for a product lifecycle by working closely with Product Managers and Solution Architects.
• Use cutting edge visualisations to enable our business/Clients to better explore the patterns and trends hidden within our data.
• Evaluate and apply machine learning algorithms on data to create models.
• Work collaboratively with data engineers and software engineers to deliver product solutions and/or prototypes.

Experience Required Essential

• 10-15 years of experience as Data Scientist

Strong grasp of numbers, statistics, mathematical concepts, and algorithms. Ideally with a degree at a Masters level.

• Knowledge of data structures, relational data, and big data platforms.
• Demonstrate experience and understanding of Machine Learning, e.g.: linear/logistics regression, random forest, SVM, neural networks, etc.

Experience with computer vison use-case.

• Proficiency with Python.
• Proficiency with machine and deep learning frameworks such as TensorFlow,Keras.
• Experience with techniques to retrieve actionable feature insight from deep neural networks.
• Experience developing solutions for on cloud.

Desirable

• Oil and Gas, utility, Telecoms or construction sector experience.
• Contribution to industry/open source communities.
• Experience of working within a multi-cultural, global environment.
• Experience of working in a fast moving and changing environment.
• Experience with NLP and linguistic approaches for retrieval, interpretation, and pushing of insight from scientific literature