{"id":4225873,"url":"https://alion.io/job/caterpillar-data-scientist-engine-data-analytics","title":"Data Scientist-Engine Data Analytics","company":{"id":176554,"name":"Caterpillar","domain":"caterpillar.com","url":"https://alion.io/company/caterpillar","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":96,"open_postings":176,"ghost_share":0,"stale_share":0.153,"repost_share":0.023,"time_to_fill_p50_days":31,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":true,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Oracle","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-11-13T07:52:20Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T07:52:20Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Career Area:\nTechnology, Digital and DataJob Description:\nYour Work Shapes the World at Caterpillar Inc.\nWhen you join Caterpillar, you're joining a global team who cares not just about the work we do - but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here - we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.\nResponsibilities\n· 3 - 7 Yrs. of work experience in data analytics (Engine-Data Analytics).\n· Must have hands on exposure in Python, Tableau, SQL and Oracle DB\n· Exposure in Automotive / Manufacturing industry\n· Directing the data gathering, data mining, and data processing processes in huge volume; creating appropriate data models.\n· Exploring, promoting, and implementing semantic data capabilities through Natural Language Processing, text analysis and machine learning techniques.\n· Leading to define requirements and scope of data analyses; presenting and reporting possible business insights to management using data visualization technologies.\n· Conducting research on data model optimization and algorithms to improve effectiveness and accuracy on data analyses.\nSkill Descriptors:\nBusiness Statistics: Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions.\nLevel Working Knowledge:\nExplains the basic decision process associated with specific statistics.\nWorks with basic statistical functions on a spreadsheet or a calculator.\nExplains reasons for common statistical errors, misinterpretations, and misrepresentations.\nDescribes characteristics of sample size, normal distributions, and standard deviation.\nGenerates and interprets basic statistical data.\nAccuracy and Attention to Detail: Understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision.\nLevel Working Knowledge:\nAccurately gauges the impact and cost of errors, omissions, and oversights.\nUtilizes specific approaches and tools for checking and cross-checking outputs.\nProcesses limited amounts of detailed information with good accuracy.\nLearns from mistakes and applies lessons learned.\nDevelops and uses checklists to ensure that information goes out error-free.\nAnalytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.\nLevel Working Knowledge:\nApproaches a situation or problem by defining the problem or issue and determining its significance.\nMakes a systematic comparison of two or more alternative solutions.\nUses flow charts, Pareto charts, fish diagrams, etc. to disclose meaningful data patterns.\nIdentifies the major forces, events and people impacting and impacted by the situation at hand.\nUses logic and intuition to make inferences about the meaning of the data and arrive at conclusions.\nMachine Learning: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.\nLevel Basic Understanding:\nExplains the definition and objectives of machine learning.\nDescribes the algorithms and logic of machine learning.\nDistinguishes between machine learning and deep learning.\nGives several examples on the implementation of machine learning.\nProgramming Languages: Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques and platforms in order to write and modify programming languages.\nLevel Basic Understanding:\nDescribes the basic concepts of programming and program construction activities.\nUses programming documentation including program specifications in order to maintain standards.\nDescribes the capabilities of major programming languages.\nIdentifies locally relevant programming tools.\nQuery and Database Access Tools: Knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use.\nLevel Working Knowledge:\nDefines, creates and tests simple queries by using associated command language in a specific environment.\nApplies appropriate query tools used to connect to the data warehouse.\nObtains and analyzes query access path information and query results.\nEmploys tested query statements to retrieve, insert, update and delete information.\nWorks with advanced features and functions including sorting, filtering and making simple calculations.\nRequirements Analysis: Knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project.\nLevel Working Knowledge:\nFollows policies, practices and standards for determining functional and informational requirements.\nConfirms deliverables associated with requirements analysis.\nCommunicates with customers and users to elicit and gather client requirements.\nParticipates in the preparation of detailed documentation and requirements.\nUtilizes specific organizational methods, tools and techniques for requirements analysis.\nAdditional information: This job requires 5 working days from office.\nThis Job Description is intended as a general guide to the job duties for this position and is intended for the purpose of establishing the specific salary grade. It is not designed to contain or be interpreted as an exhaustive summary of all responsibilities, duties and effort required of employees assigned to this job. At the discretion of management, this description may be changed at any time to address the evolving needs of the organization. It is expressly not intended to be a comprehensive list of “essential job functions” as that term is defined by the Americans with Disabilities Act.\nThis position requires working onsite five days a week.Relocation is available for this position.Posting Dates:\nCaterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply\nNot ready to apply? 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