This position is with our client who is world's largest company in the field of automobiles development and testing of powertrain system.
Leadership role in Data Science: (Reporting to CTO)
This is a lead role with all the associated managerial and strategic goals. He should have acumen to build business.
He should be able to Institutionalize the domain knowledge by producing Solutions (cross industry)
He should be hands on to create machine learning algorithms to build new products
Collaborate with business development team to understand the client challenges and come up with innovative solutions to meet their requirements
A Data story teller and an appreciation for both the power and limits of data. You will be able to communicate your findings, orally and visually.
Experience of working in an unstructured environment / startups
Drive the creation and implementation of best practices for statistical data modelling, analysis, and machine learning; data exploration and reporting tools; and processes that allow data team to work efficiently.
Significant experience managing, mentoring, and coaching teams of data scientists and analysts
You will have statistical, mathematical, predictive modelling as well as business strategy skills to build the algorithms
The ability to filter complex and seemingly arcane analytics into clear, accessible, actionable insight
Experience in finding patterns in data and creating statistical models, data exploration, data visualization and data mining
Define the overarching data strategy and vision for data pipeline, data products
Experience of overseeing Big Data projects: managing risks and data security
Experience of leading data science, data discovery and machine learning projects
The Successful Applicant
A PhD in a quantitative discipline such as computer science, statistics, physics or mathematics. MBA is a plus
15+ years of hands on experience in machine learning algorithms
Prior experience in managing teams
Excellent interpersonal and stakeholder management skills
Excellent communication skills, and ability to work across multiple teams and levels within the organisation
Understanding of good software development practices
Analytics: SQL, jupyter/ipython notebooks, re.dash
Modelling: scikit-learn, stats-models, pymc3, tensor-flow
Data Engineering: python, SQL, Spark, Scala, Docker, AWS
Data Warehouse: AWS Redshift
Dashboards: D3.js, bokeh, re.dash, Tableau