Lead Data Science T500-10208

2 weeks ago

Bengaluru, Karnataka, India Kenvue Full time

Job Overview:

We are looking for a Lead Analyst who will support our Global Data Science team with insights gained from analyzing company data.

The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action.

They must have strong experience using a variety of data mining / data analysis methods, using a variety of data tools, supporting and improving models, using / creating algorithms and creating / running simulations.

They must have a proven ability to help deliver business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams.

Responsibilities for Data Scientist:
Work with Data Science team to identify opportunities for leveraging company data to drive business solutions.

Under the guidance of regional data science team, mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.

Assist in improving the effectiveness and accuracy of existing methods and techniques.
Implement and scale custom data models and algorithms to apply to data sets.
Leverage predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
Execute company A/B testing framework and test model quality.
Coordinate with different functional teams to implement models and monitor outcomes.
Document business processes and support in in deployment of tools to monitor and analyze model performance and data accuracy.

Qualifications for Data Scientist:
Strong problem-solving skills.
Experience using statistical languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
Experience working with and creating data architectures.

Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, time series forecasting, Market mix modelling etc.) and their real-world advantages / drawbacks.

Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

Excellent written and verbal communication skills for coordinating across teams.
A drive to learn and master new technologies and techniques.


We're looking for someone with 8+ years of experience working in a similar role, has a Bachelor's degree in, Mathematics, Computer Science or another quantitative field, and is familiar with the following software / tools:Experience querying databases and using statistical computer languages: R, Python, SQL, etc.

Model Deployment experience on websites.

Experience using web services:
Redshift, S3, Spark etc.

Experience creating and using advanced machine learning algorithms and statistics:

GLM/Regression, Random Forest, Boosting, Trees, text mining, NLP, Time series forecasting, Market mix modelling, clustering, decision trees, neural networks, etc.


Experience analyzing data from 3rd party providers:
Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.

Experience with distributed data / computing tools:
Map / Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
Experience visualizing / presenting data for stakeholders.
Excel in time series problems with a proven record of a time-series forecasting product. Understand both the statistical as well as the machine learning approach to answer time-series problems.
Experience working with Retail / CPG / FMCG would be preferred.
Some experience with AWS Sagemaker and running and scaling models in production will be preferred.

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