Hewlett Packard Enterprise is hiring for an FRESHER entry level Data Scientist role in India

Position: Data Scientist

Company: Hewlett Packard Enterprise (HPE)

Location: Bengaluru, Karnataka, India

Job type: Full-time

Job mode: Onsite

Job requisition id: Not provided in the original JD

Years of experience: 0-3 years (Fresher / Entry Level)

Company Description

• Hewlett Packard Enterprise, widely recognized as HPE, stands as an industry-leading global edge-to-cloud organization dedicated to transforming how businesses connect, protect, analyze, and act on their digital assets.

• The company delivers specialized end-to-end technology solutions that enable organizations around the globe to extract actionable intelligence from vast volumes of information, driving key operational choices at the speed modern markets require.

• HPE operates on a culture grounded in continuous innovation, bold technical vision, and an unwavering commitment to discovering better methods to accelerate future technological achievements.

• Diversity and equal opportunity form the core of HPE's operational philosophy, providing a flexible environment where individuals from varied backgrounds can flourish, collaborate, and excel.

• Through its dedicated Finance and Corporate Strategy division, HPE ensures that global enterprise investments are backed by precise analytical frameworks and operationally aligned business modeling.

• The team acts as a key analytical engine that empowers decision-makers to optimize capital distribution, evaluate prospective ventures, and maximize long-term enterprise value worldwide.

• Joining HPE means becoming part of an inclusive, forward-thinking global network where professional growth, continuous educational investment, and career exploration across domains are actively nurtured.

• The organization continuously sets benchmark standards in data privacy, ethical artificial intelligence development, robust cloud architecture, and corporate social responsibility.

Profile Overview

• The Data Scientist position within the Finance and Corporate Strategy division is tailored for early-career analytics professionals eager to solve multi-faceted business challenges using scientific approaches.

• In this entry-level capacity, the selected individual will work directly on designing, constructing, and applying programmatic techniques and advanced quantitative models to convert complex data streams into actionable operational intelligence.

• The role focuses on taking raw structured and unstructured data, cleaning and organizing it, and generating clear predictive, inferential, and descriptive business insights for internal decision-makers.

• Key functions include collaborating closely with senior team members to formulate hypothesis matrices, prepare datasets for Exploratory Data Analysis, and maintain metadata infrastructure.

• The candidate will contribute directly to building statistical and machine learning models, evaluating model accuracy metrics, and selecting optimal algorithms to address finance and strategic objectives.

• Translating high-level quantitative outputs into clear visual stories, dashboards, and reports forms a fundamental expectation for this role, bridging technical analytical findings with practical commercial applications.

• The professional will assist in embedding these analytic models and workflows directly into enterprise client systems, automating processes, and improving operational efficiency across teams.

• Working as a vital contributor on projects of specialized scope, the Data Scientist will apply foundational technical knowledge to deliver recommendations, evaluate data integrity, and conduct solution validations.

• The position operates primarily on-site from HPE's modern facilities in Bengaluru, providing direct contact with cross-functional domain experts, enterprise strategists, and engineering leaders.

• Candidates will gain extensive hands-on experience across the end-to-end data science lifecycle, spanning data extraction, feature engineering, modeling, validation, and real-world deployment.

• This role acts as an ideal launching pad for analytical minds aiming to cultivate a deep specialization in financial analytics, predictive modeling, and strategic enterprise decision-making.

Qualifications

• Educational Background:

  • Candidates must possess an earned Bachelor’s degree in Statistics, Operations Research, Computer Science, Data Science, Applied Mathematics, or a closely related quantitative field.

• Technical Competencies & Mathematical Foundations:

  • Basic foundational knowledge of core data science methodologies, statistical inference, hypothesis testing, and quantitative problem-solving techniques.

  • Essential understanding of statistical modeling approaches, basic predictive algorithms, and operations research principles.

  • Exposure to foundational machine learning concepts, feature selection methods, and model evaluation techniques.

• Programming Languages & Data Science Tools:

  • Familiarity with primary analytics and data manipulation programming languages, particularly Python or R.

  • Basic practical understanding of statistical software suites, numerical libraries, and analytical toolsets such as SAS or SPSS.

  • Working knowledge of SQL for database querying, data extraction, filtering, and aggregation.

• Data Engineering & ETL Capabilities:

  • Fundamental understanding of data mapping, schema structures, data pipeline transfer mechanisms, and data migration workflows.

  • Basic familiarity with enterprise-grade Extract, Transform, Load (ETL) tools and frameworks such as Informatica, Ab Initio, or Talend.

  • Ability to ingest, sanitize, prepare, and structure raw, messy, or unstructured datasets into clean analytical tables.

• Data Visualization & Business Analytics:

  • Proficiency in basic data visualization techniques and dashboard tools to present analytical findings cleanly.

  • Ability to translate mathematical model outputs into intuitive, clear, and actionable business stories.

  • Conceptual knowledge of translating corporate strategy or business problems into concrete analytics framework objectives.

• Professional Capabilities:

  • Strong oral and written communication skills with the capacity to present quantitative concepts clearly to non-technical stakeholders.

  • Demonstrated capacity to work collaborative within a team structure, exercising independent judgment within guided project boundaries.

Additional Info

• Work Arrangement & Location Details:

  • This position is structured as a full-time, strictly on-site role operating out of HPE’s central office hub located in Bengaluru, Karnataka, India.

  • Employees are expected to work directly from the office to encourage close collaboration, real-time strategy planning, and team alignment.

• Benefits & Comprehensive Total Rewards:

  • HPE offers a robust suite of compensation packages and health benefits designed to support physical, financial, and emotional well-being for employees and dependents.

  • Team members receive access to specialized career advancement programs, skill expansion bootcamps, and cross-divisional internal career transfers.

• Inclusion & Workplace Accessibility:

  • HPE maintains an unconditionally inclusive workplace environment that actively values diversity across backgrounds, experiences, and perspectives.

  • Equal opportunity is guaranteed across all recruitment decisions regardless of race, gender, disability, status, or background, prioritizing merit and talent.

  • Candidates requiring specific workplace accommodations during the application or interview phase are provided dedicated support channels.

• Recruitment Integrity & Anti-Fraud Advisory:

  • HPE never asks for registration fees, placement payments, or monetary contributions at any point during the candidate evaluation lifecycle.

  • Official communications, interview setups, and employment offers are processed strictly through official company web domains and verified talent channels.

  • Job seekers are advised to verify all recruitment communications independently and avoid sharing sensitive personal information on unverified platforms.

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