Position:
• Data Scientist I
Company:
• Honeywell
Location:
• Bengaluru, Karnataka, India
Job Type:
• Full Time
Job Mode:
• Onsite
Job Requisition ID:
• 149401
Years of Experience:
• 0+ Years
About the Opportunity
• Honeywell is seeking an early career Data Scientist to join its growing analytics and artificial intelligence team in Bengaluru.
• This position provides an opportunity for aspiring data professionals to work on real business challenges by applying analytical thinking, statistical methods, machine learning techniques, and modern programming practices.
• The role is designed for individuals who are passionate about transforming large volumes of data into meaningful insights that can support decision making across different business functions.
• As a member of the data science team, you will collaborate with experienced professionals and business stakeholders to understand challenges, identify opportunities, and develop data driven solutions that create measurable business outcomes.
• The position offers exposure to a broad range of projects involving predictive analytics, machine learning models, statistical evaluation, process optimization, and business intelligence.
• Candidates joining this role will have the chance to learn from experienced data scientists while working on innovative initiatives that support Honeywell's mission of building smarter, safer, and more sustainable industries.
• The role is ideal for fresh graduates and early career professionals who want to establish a strong foundation in applied data science within a global technology organization.
Company Description
• Honeywell is a globally recognized technology and industrial company that delivers innovative products, software solutions, and services across multiple industries.
• The organization has built a strong reputation for helping businesses solve complex operational and technological challenges through automation, digital transformation, engineering excellence, and advanced analytics.
• With operations spanning numerous countries, Honeywell serves customers across aerospace, industrial automation, building technologies, sustainability solutions, energy management, manufacturing, logistics, and safety sectors.
• The company continuously invests in technology and innovation to help organizations improve efficiency, increase productivity, reduce operational costs, and achieve sustainability goals.
• Through advanced software platforms and connected technologies, Honeywell enables organizations to make better decisions using real time data and intelligent automation.
• Honeywell's digital solutions support enterprises in monitoring performance, optimizing operations, predicting maintenance requirements, and improving business outcomes.
• The company believes that data and technology can play a critical role in solving some of the world's most pressing challenges.
• By integrating engineering expertise with artificial intelligence, analytics, cloud technologies, and automation platforms, Honeywell continues to create solutions that improve quality of life and industrial performance.
• Employees at Honeywell have the opportunity to work on impactful projects that influence industries around the world.
• The organization promotes innovation, collaboration, continuous learning, and professional development.
• Team members are encouraged to bring new ideas, challenge traditional approaches, and contribute to initiatives that create lasting value for customers and communities.
• Honeywell's commitment to technological advancement has positioned the company as a trusted partner for organizations seeking digital transformation and operational excellence.
• The company culture emphasizes accountability, integrity, inclusion, innovation, and customer focus.
• Employees gain exposure to diverse business domains and cutting edge technologies while working alongside talented professionals from various backgrounds.
• Through its strong focus on research, innovation, and intelligent systems, Honeywell remains at the forefront of technological progress and industrial modernization.
Profile Overview
• The Data Scientist I role focuses on utilizing data science methodologies to solve business problems and generate actionable insights.
• Individuals in this position will work with structured and unstructured datasets to identify patterns, trends, relationships, and opportunities that can support strategic and operational decision making.
• The role involves applying machine learning algorithms, statistical analysis techniques, predictive modeling approaches, and analytical frameworks to extract value from data.
• Data scientists will collaborate closely with business leaders, engineers, analysts, and technical teams to understand organizational objectives and translate them into analytical solutions.
• The position requires curiosity, analytical thinking, problem solving capabilities, and a willingness to continuously learn emerging technologies and methodologies.
• Candidates will participate in the complete lifecycle of data science projects, beginning with business understanding and data collection and extending through model development, validation, deployment, and performance monitoring.
• The successful candidate will contribute to initiatives that improve efficiency, reduce operational challenges, enhance forecasting accuracy, and support business growth.
• Working in a collaborative environment, team members will have opportunities to gain hands on experience with modern tools, programming languages, machine learning frameworks, and statistical methodologies.
• The role also requires effective communication skills to present analytical findings and recommendations to both technical and nontechnical stakeholders.
• Candidates should be comfortable working with large datasets and developing scalable analytical solutions.
• The position offers significant opportunities for professional growth and exposure to real world applications of artificial intelligence and advanced analytics.
• Employees will gain practical experience in applying theoretical concepts to business situations across multiple industries.
• This role serves as an excellent entry point into a long term career in data science, analytics, machine learning, and artificial intelligence.
Key Responsibilities
Data Analysis and Exploration
• Analyze large datasets to identify meaningful trends, relationships, and insights.
• Examine structured and unstructured data sources to support business objectives.
• Conduct exploratory data analysis to understand data characteristics and quality.
• Identify anomalies, patterns, and opportunities hidden within complex datasets.
• Generate analytical reports and summaries for stakeholders.
Machine Learning Development
• Design and develop machine learning models to solve business challenges.
• Apply supervised and unsupervised learning techniques where appropriate.
• Build predictive models that improve decision making and operational performance.
• Evaluate model effectiveness using established performance metrics.
• Improve existing algorithms through testing, experimentation, and optimization.
Statistical Modeling
• Apply statistical methodologies to evaluate business scenarios.
• Use quantitative approaches to generate reliable insights and recommendations.
• Perform hypothesis testing and model validation activities.
• Support forecasting and predictive analytics initiatives.
• Interpret statistical outputs and translate findings into business language.
End to End Project Delivery
• Participate in complete data science project execution from concept through implementation.
• Understand business requirements and convert them into analytical objectives.
• Gather and prepare data for model development activities.
• Build, test, validate, and deploy analytical solutions.
• Monitor project outcomes and recommend improvements when necessary.
Cross Functional Collaboration
• Work closely with business teams to understand operational requirements.
• Collaborate with engineering and technology teams on implementation activities.
• Participate in discussions related to project priorities and business objectives.
• Communicate findings clearly to stakeholders across different functions.
• Contribute to a collaborative and knowledge sharing environment.
Problem Solving and Innovation
• Address complex business challenges using analytical methodologies.
• Apply logical reasoning and critical thinking to identify effective solutions.
• Explore innovative approaches for improving business processes.
• Support continuous improvement initiatives through data driven recommendations.
• Contribute creative ideas that help generate business value.
Team Contribution
• Support team initiatives and strategic objectives.
• Share knowledge and best practices with colleagues.
• Assist in maintaining high quality analytical standards.
• Participate in team discussions regarding technology adoption and methodology improvements.
• Contribute to the long term growth and success of the data science function.
Qualifications
Educational Background
• Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, Information Technology, or a related quantitative field.
• Candidates possessing advanced academic qualifications may also be considered.
• Strong academic understanding of mathematical and statistical concepts is beneficial.
• Exposure to data science coursework, research projects, internships, or academic assignments is advantageous.
Technical Skills
• Knowledge of programming languages such as Python or R.
• Familiarity with data manipulation and analysis techniques.
• Understanding of machine learning fundamentals and predictive modeling approaches.
• Knowledge of statistical analysis concepts and methodologies.
• Ability to work with datasets and derive meaningful insights.
• Awareness of modern analytical tools and frameworks.
Analytical Capabilities
• Strong problem solving mindset.
• Ability to interpret complex information and convert it into actionable recommendations.
• Excellent quantitative reasoning skills.
• Capability to approach challenges in a structured and logical manner.
• Interest in solving business problems using data driven techniques.
Communication Skills
• Ability to explain analytical findings clearly.
• Strong written and verbal communication capabilities.
• Comfortable interacting with stakeholders from diverse backgrounds.
• Ability to present recommendations and insights effectively.
• Willingness to collaborate in team based environments.
Professional Attributes
• Curiosity and eagerness to learn.
• Positive attitude toward innovation and experimentation.
• Strong attention to detail.
• Commitment to delivering high quality work.
• Ability to manage priorities and meet project expectations.
• Adaptability in a dynamic business environment.
Additional Information
• This opportunity is open to both internal and external applicants.
• The role provides an excellent platform for fresh graduates seeking practical experience in data science.
• Candidates will gain exposure to real world business challenges across multiple industries.
• The position offers opportunities to work with experienced professionals and subject matter experts.
• Employees will have access to modern technologies, analytical tools, and business datasets.
• Honeywell encourages innovation and supports continuous professional development.
• Team members are expected to contribute to a culture of collaboration and knowledge sharing.
• The organization values diverse perspectives and promotes an inclusive workplace environment.
• Successful candidates will have opportunities to build expertise in machine learning, analytics, artificial intelligence, and statistical modeling.
• The role can serve as a foundation for future growth into advanced data science, artificial intelligence, analytics leadership, and technology strategy positions.
• Individuals who enjoy working with data, solving challenging problems, and creating measurable business impact are likely to find this position rewarding.
• The role combines technical learning, business exposure, and professional development within one of the world's leading technology organizations.
• Candidates joining the team will become part of a mission focused on innovation, operational excellence, sustainability, and digital transformation.
• Through continuous learning and practical experience, employees can build a strong and successful career within Honeywell's global ecosystem.
• This opportunity is particularly suitable for individuals looking to begin their journey in data science while contributing to projects that create tangible business value and support technological advancement across industries.
Please click here to apply.
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