Data Science - Manufacturing/IOT/Utility Analytics- Manager

Bengaluru (SDC) - Eagle Ridge at Embassy Golf Links Business Park

PwC

We are a community of solvers combining human ingenuity, experience and technology innovation to help organisations build trust and deliver sustained outcomes.

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Line of Service

Advisory

Industry/Sector

Not Applicable

Specialism

Data, Analytics & AI

Management Level

Manager

Job Description & Summary

A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.

As part of our Analytics and Insights Consumption team, you’ll analyze data to drive useful insights for clients to address core business issues or to drive strategic outcomes. You'll use visualization, statistical and analytics models, AI/ML techniques, Modelops and other techniques to develop these insights.

Years of Experience: Candidates with 8+ years of hands on experience

Must Have:

  • In-depth understanding of manufacturing industry (various manufacturing processes, manufacturing operations, production workflows, and supply chain dynamics) & utility industry (including energy, water, or telecommunications), to effectively analyze data within the context of regulatory frameworks, operational challenges, and industry trends

  • Understanding of IoT architectures and protocols, experience working with sensor data and familiarity with IoT platforms and tools

  • Proficiency in statistical methods and techniques for analyzing data sets, including regression analysis, time series analysis, hypothesis testing, and predictive modeling

  • Strong understanding and hands-on experience with machine learning algorithms and techniques such as supervised and unsupervised learning, classification, clustering, and anomaly detection

  • Experience in Data analysis For e.g: data cleansing, standardization and data preparation for the machine learning use cases

  • Proficient in working with relational databases (e.g., SQL) and NoSQL databases

  • Experience with data warehousing and data lakes

  • Experience in machine learning frameworks and tools (For e.g. scikit-learn, mlr, caret, H2O, TensorFlow, Pytorch,  MLlib)

  • Advanced level programming in SQL or Python/Pyspark 

  • Expertise with visualization tools For e.g: Tableau, PowerBI, AWS QuickSight etc. 

Nice to have:

  • Experience in building ML models in cloud environments (At least 1 of the 3: Azure ML, GCP’s Vertex AI platform, AWS SageMaker)

  • Working knowledge of containerization ( e.g. AWS EKS, Kubernetes), Dockers and data pipeline orchestration (e.g. Airflow)

  • Good Communication and presentation skills

Education (if blank, degree and/or field of study not specified)

Degrees/Field of Study required:

Degrees/Field of Study preferred:

Certifications (if blank, certifications not specified)

Required Skills

Optional Skills

Desired Languages (If blank, desired languages not specified)

Travel Requirements

0%

Available for Work Visa Sponsorship?

No

Government Clearance Required?

No

Job Posting End Date

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Airflow Architecture AWS Azure Business Intelligence Classification Clustering Data analysis Data Analytics Data management Data Warehousing GCP Kubernetes Machine Learning ML models NoSQL Power BI Predictive modeling PySpark Python PyTorch QuickSight RDBMS SageMaker Scikit-learn SQL Statistics Tableau TensorFlow Testing Unsupervised Learning Vertex AI

Perks/benefits: Career development

Region: Asia/Pacific
Country: India
Job stats:  3  0  0

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