Advisor Data Sciences

Key Skills

AWS, Azure, Big Data Technology, Data Analytics, Data science techniques, Deep Learning, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, R Programming, SparkML, SQL, TensorFlow

Job Description

We are seeking a talented and experienced Data Scientist to join our dynamic team. The ideal candidate will be passionate about extracting actionable insights from complex datasets and developing predictive models to drive business outcomes. As a Data Scientist, you will play a key role in analyzing large volumes of data, building machine learning models, and delivering data-driven solutions to solve real-world problems.

Your role in our mission

• Lead large data science projects and deliver innovative technical solutions to solve problems and improve business outcomes

• Design, develop, test, validate, and deploy Machine Learning (ML) /Statistical models to not only learn from our vast amounts of data but to build new products

• Work closely with engineers to deploy models to production both in batch and real time while systematically tracking model performance

• Build complex data sets from multiple data sources and write complex data flows using SQL, Spark and scripting languages (e.g., Python, R)

• Use data visualization tools (e.g., Tableau, Kibana, Zeppelin) to share ongoing insights

• Present findings to both technical and non-technical audiences

• Function as a subject matter expert on machine learning and predictive modeling

• Assist engagements with key business stakeholders in discussion on business opportunities

• Be an evangelist driving wider adoption of analytics across the enterprise

• Knowledge, Skills and Abilities:

• Ability to deliver on large scale data science projects

• Ability to translate business customer problems and questions into clear requirements for analysis

• Ability to use data visualization tools proficiently

• Ability to build complex data sets from multiple data sources and write complex data flows

• Ability to write complex and efficient SQL code freehand from scratch

• Ability to wrangle and analyze data using Python or R

• Strong understanding of statistics and probability

• Proficient in Microsoft Power Point, Outlook and Word

• Ability to work under pressure while managing competing demands and deadlines

• Good understanding of Agile methodology

• Experience with machine learning is a plus

What we're looking for

Qualifications

Minimum Education

• Bachelor’s Degree in Computer Science, Statistics, Applied Mathematics, or relevant major required.

• S., or PhD. in Statistics, Computer Science, Mathematics, Physics, Economics, or other quantitative field preferred.

• Minimum Related Work Experience

• 10 years’ of industry experience in Data Science/Machine Learning as a mid-senior data scientist/technical lead developing ML models with business impact.

• 10+ years’ hands-on, industry experience with data & languages such as SQL, Python, R, Scala

• Good experience in data analysis using Relational Databases, SQL, & Hadoop

• Good experience in leading complex data science projects from development to production, end-to-end

• Good experience in designing and implementing ML pipelines in production environments

• Good experience with Apache Spark (including Datasets, SparkML) and other Big Data analytics tools (e.g. Hadoop ecosystem, PySpark, GraphML)

• Experience with 2 or more additional modeling techniques (i.e. Natural Language Processing, Deep Learning, Time Series Analysis, Optimization algorithms) is a plus

• Experience with one or more deep learning libraries (e.g., TensorFlow, PyTorch, Caffe) is a plus.

• Experience implementing solutions in a cloud environment (AWS or Azure) is a plus.

• Experience from working in Lean and Agile environments is a plus.

Work Environment

Fast-Paced, Challenging and rewarding work environment. Will require late evening work to overlap US work hours.

Work Location: Anywhere across India

What you should expect in this role

Fast-paced,challenging and rewarding work environment.

Hybrid Office environment.

Will require late evening work to overlap US work hours.