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28/08 HR
HR at Michael Page

Views:367 Applications:66 Rec. Actions:Recruiter Actions:0

Data Science Lead - Chemicals (8-12 yrs)

Chennai Job Code: 844152

Industry - Chemicals / Petrochemical / Plastic / Rubber

Category - Consulting

Job Type - Permanent

Job Description :


- As Data Science Leader, you will lead the development of Data Science COE at Chennai facility and develop data strategy for a chemical company in the middle of a digital transformation of its businesses and focused on building the capabilities and tools in support of this.


Client Details

Our client is a global speciality chemical company with headquarters in United States committed to safeguarding the environment, maintaining safety in the workplace, and promoting sustainable development. It delivers exceptional service and innovative solutions to our customers globally in the pulp and paper, leather, and water treatment sectors to help boost productivity, reduce risk, improve product quality, and provide a measurable return on investment.

Description

As Data Science Leader, you will lead the data science program and work closely with client stakeholders to derive deep industry knowledge across paper, water, leather, and performance chemical industries.

The range of responsibilities includes include but not limited to:

- Develop a data strategy for the company including collection of the right data, creation of the data science project portfolio, partnering with external providers, and augmenting capabilities with additional internal hire

- Communicate and develop relationship with key stakeholders and subject matter experts to tee up proofs of concept projects to solve complex data science problems


- Individual expertise, breadth of data science knowledge, and ability to partner with external companies will be essential for success


- In addition to the pure data science problems, you will be working closely with a multi-disciplinary team consisting of sensor scientists, software engineers, network engineers, mechanical/electrical engineers, and chemical engineers in the development, and deployment of IoT solutions.


Profile

The ideal candidate for the Data Science Lead should have:

- Bachelor's degree in a quantitative field such as Data Science, Statistics, Applied Mathematics, Physics, Engineering, or Computer Science

- Master's or PhD degree in a quantitative field such as Data Science, Statistics, Applied Mathematics, Physics, Engineering, or Computer Science


- 8+ years of relevant working experience in an analytical role involving data extraction, analysis, and visualisation in which 3 plus years is of managing Data science teams


- Expertise in one or more programming languages R, Python, MATLAB, JMP, Minitab, Java, C++, Scala


- Key libraries such as Sklearn, XgBoost, GLMNet, Dplyr, ggplot, Rshiny


- Experience and knowledge of data mining algorithms including supervised and unsupervised machine learning techniques areas such as Gradient Boosting, Decision Trees, Multivariate Regressions, Logistic regressions, Neural Network, Random Forest, Support Vector Machine, Naive Bayes, Time Series, Optimisation


- Microsoft IoT/data science toolkit: Azure Machine Learning, Datalake, Datalake analytics,


- Workbench, IoT Hub, Stream Analytics, CosmosDB, Time Series Insights, PowerBI


- Data querying languages (e.g. SQL, Hadoop/Hive) and Preferred Qualifications


Job Offer

As the Data Science Lead, you will be working for an entrepreneurial company with a Sustainability mission and digital ambitions at the core of its strategy. A strong business focus, ownership and inner self-drive to solve real-world impactful problems with innovative digital solutions.

To apply online please click the 'Apply' button below. For a confidential discussion about this role please contact Damini Sarin on +91 124 452 5447.

Contact - Damini Sarin - +91 124 452 5447

The Apply Button will redirect you to website. Please apply there as well.

This job opening was posted long time back. It may not be active. Nor was it removed by the recruiter. Please use your discretion.

Women-friendly workplace:

Maternity and Paternity Benefits

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