Job Description

PRIMARY RESPONSIBILITIES

Understand Business problems and KPIs by holding discussions with relevant customer stakeholders

Prescribe the right data science approach to solve customers Business problems

Identify the different data sources needed for project execution including both internal and external

data

Ensure proper DQ checks are done and the data is well understood by the Team

Document DQ related issues and barriers and take it up with Customer stakeholders

Generate hypothesis for performing various Exploratory analysis and lead the effort

Storyboard the findings in data and explain the Business value convincingly to customers

Drive analytical modeling using a variety of learning algorithms and ability to compare model outputs

without Bias

Demonstrate Business value of Analytical models and ensure they are deployed in Production

Prescribe the right Data technologies to use in Production and lead the Data pipelining effort for

production

Orchestrate Data and ML solutions using Cloud services

Employ CI/CD practices in Model deployment and produce a state-of-art model deployment that can

be Traceable

Be the anchor for Customer calls and ensure customer communication is effective

Ensure that right coding guidelines and processes are followed by the Team

Institutionalize good Data Science practices in the Team

Ensure proper documentation via good project management tools like Confluence, JIRA etc.

Author Technical blogs both internally and externally and evangelize the Teams efforts

EXPERIENCE

BS/MS in Computer Science, Math, Physics, Engineering, Statistics or other quantitative or

computational field. Advanced degrees preferred

Should know what model to apply and in what situation to apply (know advantages and dis

advantages of ML /DL techniques)

Proven ability to perform in-depth analysis, compile and interpret results

Demonstrate proficiency with various approaches in regression, classification, and

cluster analysis

Good understanding of applied statistics, such as probability distributions, measures of

dispersion and central tendency, hypothesis testing and statistical inferences.

Demonstrate proficiency in at least one Deep learning technologies

Demonstrated Experience in at least in one of the following NLP/computer

vision/operations research/data mining/ML/AI

Must have experience ML models in R/ Python

Demonstrable strength in programming in Python/R/Scala

Should have good experience in Object oriente technologies and Design

Experience with one or more data visualization tool / library such as Tableau, R Shiny, Seaborn,

etc

Expertise in SQL programming languages and familiarity with Hive, Pig

Excellent quantitative skills and the ability to tell a story using data

Strong communication and presentation skills

Ability to initiate and drive projects from conception to completion with minimal guidance

Passionate about turning data into actionable insights

GOOD TO HAVE:

M.S. in Computer Science, Math, Physics, Engineering, Statistics or other quantitative or

computational field

Expertise in application of machine learning algorithms on large datasets

Experience with large datasets and distributed computing (Hadoop, Spark) a plus

Experience accessing data, map-reduce programming style and training models in Hadoop,

Spark

Experience in deploying models in cloud platforms such as Google Cloud/Microsoft Azure/AWS

is a plus

Nice to have knowledge of NoSQL DBs like MongoDB, Cassandra and HBase

Contribution to research community reflected in publications in top conferences/Kaggle

competitions

Knowledge of latest DL technologies

PERSONAL ATTRIBUTES

Strong written and verbal communication skills

Articulation skills

Good team player

Self-starter who requires minimal oversight

Ability to prioritize and manage multiple tasks

Process orientation and the ability to define and set up processes

EXPERIENCE

10+ years with at least 7+ years of DS

experience

LOCATION

Gurgaon, Bangalore