Sr. Data Scientist – ML Ops Job

YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation.

At YASH, we’re a cluster of the brightest stars working with cutting-edge technologies. Our purpose is anchored in a single truth – bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future.

We are looking forward to hire Machine Learning (ML) Professionals in the following areas :

Experience

5-8 Years

Job Description

Role: Machine Learning Developer

Total Experience: 5-8 years

As a Developer for machine learning, you will work in a team of  experienced researchers, data scientists and application 
developers taking on challenges posed by the Yash customers and product units.

You will work together with a team of dedicated experts including researchers, developers, DevOps engineers, and architects with a single goal of building best machine learning pipelines for a variety of use cases spanning commerce, agriculture, Insurance, financial markets, and procurement. You will have the chance to work with the richest data sets available in the world addressing real-world problems. Your primary goal will be to implement state-of-the-art algorithms and to develop new approaches and technologies for deriving value from our customers’ data.

You will have a chance to select and implement the best technologies and approaches based on your own experience, judgment, and experimentation results. This role combines:

• Experience with Machine Learning, NLP, Deep Learning Practical knowledge of working with scalable platforms for processing of huge data sets, 
• Ability to understand the data, associated processes and business implications, 
• Scaling from minimum viable product up to shippable production code, 
• Build and maintaining innovative new products from the ground-up.

Key Responsibilities

• Push the frontiers of what is possible in the area of  machine learning to create new Incubation
•  Explore, understand, and implement most recent algorithms and approaches for supervised and unsupervised machine learning and deep learning 
• Comfortably handle multi-terabyte data sets in scale-up and scale-out environments 
• Understand business processes which create and consume data to be able to select best approaches, evaluate their performance, and assess business relevance 
• Create excellence both in terms of results quality and system scalability through continuous evaluation, analysis, and refinement of the system implementation 
• Communicate the relevance of implemented systems and achieved results in a visual and consistent way
• Work closely with the team (product owner, designers, and other developers) and customers to holistically understand business and user requirements, and derive adequate application development concepts 
• Performing quality assurance tasks 
• Working together with partners and customers 
• Solve complex integration issues 
• Ability to work in global teams with different time zones 
• Immerse yourself quickly in new topics, terminology and development tasks
   

Job Role and Skills required

Quick List

Role
Total Exp
Must to have
Good to have

Data Scientist (AI)
5-8 Years

Min 3+ years of relevant experience in data analytics

•  Experience in developing minimum viable product related to data analytics
• Qualification in statistics or mathematics
•  Any data science certifications
•  Good understanding on ML & DL algorithms and frameworks (Scikit-learn, Tensorflow/Keras/ PyTorch/ H2O etc.)
• Should have worked on diverse projects related to NLP and computer vision
• Well versed with data science methodologies and frameworks (NLTK, RASA, Spacy, OpenCV, Scikit-learn, Tensorflow)
• Good proficiency on Python/ R/ Tableau/Power BI etc.
• Understanding of RDBMS concepts – SQL, Oracle
• Willing to work in a challenging environment
• Strong communication skills

• Experience on prescriptive analytics
• Experience on web frameworks like R-Shiny, Flask or Django
• Experience in developing Machine Learning models on the cloud (Azure, GCP or AWS)
• Domain experience in manufacturing industry
• Understanding of No-SQL databases – MongoDB, Cassandra, Neo4j

Minimum Qualifications, Skills

• Degree in Computer Science, Information Technology, 
• Data Science, Mathematics, Statistics, Operations Research or related field 
• Track record of developing novel learning algorithms and/or systems 
• Proficiency in handling of multi-terabyte datasets in big data frameworks 
• Experience with Machine and Deep Learning software packages & libraries such as Keras, TensorFlow, Scikitlearn, Spacy, NLTK, RASA, Spacy, DeepLearning4j, Caffe, Torch, Theano, etc; programming languages such as Python is must. 
• Ability to visualize data and present core insights in a clear and compelling way 
• Ability to understand business processes and drive to solve business problems
• Experience in Cloud like Azure, AWS and GCP is plus. 
• Excellent with written and verbal communication and attitude to thrive in a fun, fast-paced startup-like environment.
• An attention to detail with self-discipline and a drive for results
• Demonstrated ability to work in ambiguous situations
• Good at conceptualization and execution of projects
• Strong business acumen to connect technology and business
• Good Time Management skills – ability to prioritize tasks and projects
• Proactive approach to problem resolution, suggesting alternate solutions
• Be able to work under tight deadlines & pressure without compromising on quality
• Good communication and Strong Interpersonal Skills
• Worked in distributed/cross-functional teams
• Positive attitude and a team player

At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale.

Our Hyperlearning workplace is grounded upon four principles

• Flexible work arrangements, Free spirit, and emotional positivity
• Agile self-determination, trust, transparency, and open collaboration
• All Support needed for the realization of business goals,
• Stable employment with a great atmosphere and ethical corporate culture