Data Scientist – Vehicle Engineering CAST

Data Scientist – Vehicle Engineering CAST (DS VEC)
Mission
The mission for a Data Scientist within Vehicle Engineering (DS VEC) is to perform Autonomously and flexibly carry out advanced analytics in multiple domains and environments. Run advanced modeling on data in order to extract knowledge and/or predict future events. Autonomously create and develop concepts. Understand the complete analytics chain from storing, structuring, modeling, to visualizing and translating data into actionable insights. Review, advice and communicate in analytics use cases.

This analysis is done at vehicle level for various features that enable more benefits for customer, Environment, Safety and for our unique selling points.

Since this analysis are performed at vehicle level, need is to keep such initiatives together across organization with CAST approach and a roadmap establishment.

Responsibilities
As a CAST team together,
    • Lead, develop drive and manage the Data Analytics for the CAST system covering the Volvo group
    • Collect, analyze and synthesize global application and customer usage,
    • Support with platform analytics and vehicle performance analysis in and in-between streams.
    • Provide tools, models, methods, way of working and expertise/educations to enable efficient vehicle performance analysis and analytics.
    • Ambition is to be recognized go-to/front face organization within Vehicle Engineering for vehicle analytics and performance evaluations.
  • As a Data Scientist,
    • Being part of CAST team, this role also demands to synchronize various initiatives at different function & Commodity level through dedicated forums & networks.
    • As coverage, it extends from base vehicle to latest offering on Electromobility, Automated vehicle, ADAS, etc. This analysis triggers innovation and concepts evaluation.
    • Data Scientist to handle the lead positions and work with entry level Data Analyst & Data Engineer on deliveries.
    • Platform thinking: Establish analysis methods and tools and set a direction to the organization.
    • Platform thinking: Apply CAST thoughts on Analysis Focus areas & Coverage, Tools, Methods, Analysis outcome Exchanges & Connecting various initiatives across organization.
    • Platform thinking: Use of global forums like Data Analysis Ambassador network to anchor and set direction for data analysis future.
    • Needs to work closely with Vehicle engineering, Vehicle technology and digital engineering streams.
    • Handle data like existing vehicle data, warranty data, Test vehicle data and additional data collected with special loggers on different applications and regions.
    • Supports the vehicle product strategy with analysis outcome, roadmap and inputs received from different streams.
    • Extend the outcome of analysis towards other business ideas on service offering.

Competence
  • Strong Leadership skills that align to flat and open office environment. Demonstrating right Leadership and Behavior with rest of the team. Person works with mutual interest of the project deliveries and organization than individual benefits.
  • BE/BTech/ME/MTech in Engineering and a specialization on data analysis.
  • Agile & SAFe certification is desired
  • Minimum of 3 to 4 years of experience in Data Analysis or Simulation and another 5 to 7 years of experience in automotive product development.
  • Programming and Data modelling: Skilled in two or three of the followings: SQL, Python, SPSS Modeler, R, etc.
  • Statistical knowledge: Knowledge in statistical models and Machine learning techniques (Supervised and Unsupervised algorithms such as Regression, Random trees, C&R Tree, CHAID, K-Means, etc).
  • Visualization : Skilled in using Visualization tools: QlikView, Power BI, etc.
  • Knowledge in data bases: Basic knowledge about VOLVO documentation systems such as SEWS2, KOLA, EDB, etc. Basic knowledge about SQL servers and Volvo Data bases (How to find and extract needed data in LDA_AutoETL, Netezza, Azure Data lake, etc).
  • Domain knowledge : Knowledge about product/component/system/market /etc. which is subjected for analytics.
  • High customer and business focus.
  • Strong networking abilities and communication skills adept in multicultural environment.
  • Complete Vehicle knowledge is a need, commodity knowledge is an advantage.
  • Good design & analysis knowledge to perform the design reviews to the team.
  • Self-driven and initiative taker.
  • Extending the involvement in other organizational activities like, Innovation Drive, Technical Design and development, Platform coordination, etc
  • Supporting Line managers with future strategic, Team competency feedback, Components roadmap inputs/ feedbacks, Customer feedback, etc
  • A combination of personal characteristics, practical experience and theoretical knowledge decides complexity and size of project scope that PM handles.
Reporting To
  • Data Scientist reports to the line Manager with in PVA Organization.
  • Functionally report to CAST global setup and to VE Site management team locally.



The Volvo Group drives prosperity through transport solutions, offering trucks, buses, construction equipment, power solutions for marine and industrial applications, financing and services that increase our customers’ uptime and productivity. Founded in 1927, the Volvo Group is committed to shaping the future landscape of sustainable transport and infrastructure solutions. Countless career opportunities are offered across the group’s leading brands - Volvo, Volvo Penta, Terex Trucks, SDLG, Renault Trucks, Prevost, Nova Bus, Mack, Eicher, Dongfeng Trucks and Arquus.

Volvo Group Trucks Technology provides Volvo Group Trucks and Business Area's with state-of-the-art research, cutting-edge engineering, product planning and purchasing services, as well as aftermarket product support. With Volvo Group Trucks Technology you will be part of a global and diverse team of highly skilled professionals who work with passion, trust each other and embrace change to stay ahead. We make our customers win.

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