Ford Motor Company is hiring for a fresher entry level AI Data Scientist role in India

Position:
AI Data Scientist

Company:
Ford Motor Company

Location:
Chennai, Tamil Nadu, India

Job type:
Full-time

Job mode:
Hybrid

Job requisition id:
54097

Years of experience:
0–3 years

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Company Description

• Ford Motor Company is a global leader in mobility, technology, and innovation, operating in more than 100 countries with a mission to shape the future of transportation.

• The company integrates advanced data, analytics, and artificial intelligence to design next-generation vehicles and digital experiences.

• Ford’s technology and enterprise teams work together to build safe, efficient, and intelligent mobility systems, driving digital transformation in every area of the business.

• The organization fosters a culture of learning, collaboration, and integrity, empowering individuals to innovate and contribute to solving complex global challenges.

• With a commitment to sustainability, Ford invests in electric mobility, AI-driven automation, and cybersecurity, ensuring reliability and safety for customers and partners worldwide.

• Employees at Ford benefit from exposure to global projects, mentorship from seasoned professionals, and opportunities to explore emerging technologies in AI, analytics, and automation.

• The Chennai Technology Center acts as a hub for innovation, enabling collaboration across product development, data science, and cybersecurity domains.

• Ford’s focus on human-centered design, continuous improvement, and digital resilience makes it an excellent place for aspiring data scientists to start their careers in applied AI and security analytics.

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Profile Overview

• The AI Data Scientist will be part of the AIOps Cybersecurity division, a critical segment that merges artificial intelligence with security operations.

• The role involves using data-driven methods to anticipate, identify, and mitigate potential cybersecurity threats and breaches.

• The position provides hands-on experience in handling large-scale data sets such as network logs, system alerts, and endpoint telemetry.

• The candidate will contribute to building predictive models that enhance risk scoring, vulnerability detection, and incident response capabilities.

• Collaboration is central to this role, as the data scientist will work closely with data engineers, cybersecurity experts, and analysts to build end-to-end analytical solutions.

• It involves applying statistical and machine learning techniques to detect anomalies, classify threat patterns, and improve system resilience.

• Candidates will also engage in continuous model improvement, performance evaluation, and automation of analytical pipelines.

• The position serves as an entry point into the evolving intersection of AI and cybersecurity, providing opportunities to learn from experts and apply research into real-world threat management contexts.

• Beyond model development, the role requires effective communication of insights through dashboards, presentations, and reports for decision-makers and technical teams.

• This profile is ideal for fresh graduates or early-career professionals passionate about data science applications in cyber defense and enterprise AI.

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Responsibilities

• Assist in collecting, cleaning, and preprocessing structured and unstructured cybersecurity data from multiple sources, such as logs, sensor outputs, and third-party feeds.

• Conduct exploratory data analysis to identify trends, outliers, and suspicious patterns that may signal potential vulnerabilities or intrusions.

• Design and implement machine learning models for anomaly detection, classification, clustering, and predictive analysis within cybersecurity environments.

• Collaborate with engineers to integrate AI models with existing AIOps systems, ensuring scalability and real-time performance.

• Develop and test algorithms that can automatically identify threats and prioritize responses based on risk scores.

• Leverage agentic AI frameworks to enhance the adaptive learning capability of threat detection models.

• Evaluate model performance and recalibrate algorithms to maintain reliability and accuracy over time.

• Create dashboards, reports, and visualizations that communicate findings and insights to technical and business stakeholders.

• Maintain thorough documentation of data pipelines, modeling techniques, assumptions, and performance metrics.

• Stay informed about the latest developments in AI, machine learning, cybersecurity practices, and threat intelligence frameworks.

• Collaborate across teams to align model outputs with security operations, incident response strategies, and enterprise risk assessments.

• Participate in regular model review sessions to ensure ethical AI use, bias control, and compliance with security policies.

• Support the integration of AI analytics into tools like SIEM and EDR to automate monitoring and detection.

• Engage in knowledge-sharing sessions and contribute to continuous learning within the AIOps cybersecurity community at Ford.

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Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Cybersecurity, or a closely related technical field.

• Proficiency in Python and familiarity with major data science libraries including NumPy, Pandas, and Scikit-learn.

• Basic understanding of supervised and unsupervised learning techniques such as linear regression, decision trees, k-means clustering, and SVMs.

• Exposure to data visualization libraries and platforms like Matplotlib, Seaborn, Power BI, or Qlik.

• Familiarity with the ETL process and MLOps lifecycle for managing and deploying models.

• Understanding of big data ecosystems like Hadoop or Spark is beneficial.

• Foundational knowledge of cybersecurity principles including attack vectors, system vulnerabilities, and defense mechanisms.

• Awareness of key cybersecurity tools such as SIEM (Security Information and Event Management) and EDR (Endpoint Detection and Response).

• Interest in learning about threat intelligence, vulnerability assessment, and incident management.

• Strong analytical thinking, curiosity, and problem-solving mindset.

• Effective written and verbal communication skills for collaboration across interdisciplinary teams.

• Ability to manage tasks independently and adapt to dynamic priorities within a hybrid work setting.

• Enthusiasm to learn new technologies, explore AI-driven cybersecurity methods, and contribute to Ford’s mission of digital security excellence.

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Additional Info

• Job Category: Enterprise Technology

• Posting Date: October 29, 2025

• Application Deadline: November 8, 2025

• Work Schedule: Full-time, hybrid arrangement at the Chennai office

• Degree Level Required: Bachelor’s or equivalent in Engineering, Computer Science, or Data Science

• Reporting Structure: Works under senior data scientists and cybersecurity leads within the global technology division

• Key Collaborators: Cybersecurity analysts, AIOps engineers, and platform integration teams

• Exposure Areas: Threat modeling, data pipeline development, risk analytics, and AI-powered automation in cybersecurity

• Tools & Platforms: Python, Spark, Power BI, SIEM platforms, internal AI frameworks

• Work Environment: Hybrid model allowing both remote collaboration and in-office engagement for project discussions and deployments

• Learning & Growth: Mentorship, on-the-job training, and opportunities to work on global-scale AI projects in cybersecurity

• Performance Metrics: Model accuracy, false positive reduction, responsiveness to incidents, and contribution to continuous improvement initiatives

• This role serves as an excellent entry-level position for candidates aspiring to specialize in AI-driven cybersecurity solutions within a large-scale enterprise setting.

Please click here to apply.