Excited to join us at Accenture and work with around 200 brightest minds, most capable individuals, and technologists? Are you keen to work closely and learn from global experts, drive innovation hands-on and shape the future together with a diverse team and our clients to improve the way we work and live?
If you have an almost unlimited energy, huge curiosity, entrepreneurial attitude, and love to work in teams, then you need to join us.
Key Responsibilities
Partner with client (product and marketing) teams to understand business problems and marketing strategies as well as engaging with IT to unearth trends in behavior.
Translate open ended business problems in analytical hypothesis and test the hypothesis leveraging various data sources.
Work through the phases of a data science project
Define data requirements for creating a model and understand the business problem
Clean, aggregate, analyze, interpret data and carry out quality analysis of it
Set up data for predictive/prescriptive analysis
Development of AI/ML models or statistical/econometric models.
Articulate strategic recommendations based on analysis and sound findings
Develop visualizations for stakeholders highlighting nuggets of interest.
The role will play a key part in monitoring the teams progress towards developing new, innovative and impactful solutions including delivering them.
Mentoring of junior level staff.
Build and develop client relationships.
Qualification: Degree preferred in Engineering (electrical, mining, chemical etc), Data Science, Statistics or related field with excellent academic performance.
Skills requirement:
Strong passion any of the following topics Advanced Data Analytics, Machine Learning, Data Science and Data Management.
Strong knowledge of technology trends across IT and digital and how they can be applied to companies to address real world problems and opportunities.
Undertaking data collection, preprocessing and analysis.
Building of statistical models to address business problems.
Well articulation and presentation of information using data visualization techniques.
Team oriented and collaborative working style, both with clients and those within the organization.
Demonstrated ability to build relationships at relevant levels within client orga
Machine Learning (R, Python, SAS, SPSS)
Big Data (Spark, Hadoop, NoSQL Databases, Data Lakes & Platforms)
Cloud Platforms (Azure, Google Cloud, AWS) with exposure to RDBMS tools like SQL, Oracle and SAP.
Experience in data preparation, analysis in Hive/Spark or similar big data analytics tool leveraging Databricks
Business Intelligence (Power BI, Tableau, Qlik)
Good grasp of machine learning, development cycle & MLOps, such as model development, model deployment, data versioning etc.
Experience:
2-4 years of professional experience in Resources / Mining
Demonstrated ability in the application of Machine Learning to real-world industrial settings with large scale data (in the mining, chemical or Oil & gas industry).
Experience with applying of machine learning to process optimization or preventative maintenance.
Experience extracting, cleaning, and processing sensors data and working with historian systems such as PI.
Occupation:
Management, human resources jobs
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