Associate Lead Data scientist 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 : 8+ years of experience

Role: Associate Lead Data Scientist

Job Description
 

• Responsible for Data and Analytics insights delivery to business owner/client.
• Drive significant impact and value in building, growing Data Science Centre of Excellence.
• Provide machine learning methodology leadership.
• Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
• Work with fellow data scientists/SW engineers to buildout other parts of the infrastructure, effectively communicating your needs and understanding theirs
• and address external and internal shareholder's product challenges.
• Practical experience in feature engineering and evaluation, automation of such tasks, model interpretation & visualization.
• Experience or willingness to learn and work in Agile and iterative development.
• Strong drive to learn and master new technologies and techniques.
• Deep understanding of data structures, algorithms, and excellent problem-solving skills.
• Willing to work in fast-paced work environment.
• Partner with the business to understand the questions they are trying to address to unlock value, and the data they have or need to collect to address the question.
• Engage on a regular basis to refine opportunities and develop a pathway for value generating data projects.
• Assist in designing data capture / experimental setups for exploratory work, or changes in process / data capture in existing systems.
• Perform exploratory data analysis, using R or Python,and provide rapid iterations of analysis to refine posed problems, and identify potential solutions.
• Develop statistical models, algorithms and/or machine learning algorithms to analyse data and address a particular business question.
• Assist and supervise Data Engineers in developing and deploying production workflows for taking data in realtime or periodically from sites / business functions,
• passing the data through the developed models and producing the relevant reporting without human intervention.
• Work with and support data team in architecture of data warehousing and data-lake as required.
• Support the Model Architect within the relevant features to design training and deployment approaches for data science and machine learning model components.
• Perform solution research and rapid iterations of development to refine posed problems and identify potential solutions.

Key Responsibilities

• Manage delivery of analytical projects in partnership with business and IT
• Own KPI and business performance metrics jointly with business partners.
• Conduct advanced statistical analysis to provide actionable insights and identify trends.
• Build models with Python and machine learning libraries (Numpy, Pandas, Scikit Learn, Tensorflow, PyTorch)
• Building core of Artificial Intelligence and Cognitive Service as Vision, Text, NLP, NLU, and others.
• Capable of quickly becoming familiar with new approaches to Machine Learning.
• Exploring or working on some of the latest advancements in the deep learning space like TensorFlow, PyTorch

Minimum Qualifications, Skills

• Bachelor’s degree in physics, Mathematics, Engineering, Metallurgy or Computer Science.
• MSc in relevant field - Physics, Mathematics, Engineering, Computer Science, Chemistry or Metallurgy.
• 8+ years of experience in Data science and Analytics delivery
• Deep knowledge of machine learning, statistics, optimization and related fields
• Hands on and deep expertise with R, Python programming.
• Machine learning skills: Experience with Natural Language Processing (NLP), Text mining, Text processing
• Deep learning skills: Understanding of deep learning techniques and experience with deep learning frameworks like TensorFlow, keras, Theano, Pytorch etc.
• Experience working with large data sets (Knowledge on getting data from cloud, Hadoop ecosystem)
• Data Visualization - Experience in one or more Data Visualization tools (MS Power BI, Tableau etc.)
• Data engineering - Hands-on in SQL and experienced in working with RDBMS for data extraction and data read/write. 
• Understanding of Data Warehouse fundamentals (architectural layers & schema types) is a plus.
• Experience productionizing Machine Learning models, in the cloud (Azure, GCP or AWS preferred)
• Domain Experience in manufacturing industry, preferred.
• Demonstrated ability to nurture and lead technical talent.
• Track record of leading and successfully completing complex data science projects.
• 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

Quick list for screening candidates:

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