Data Scientist - Junior

As a Junior Data Scientist at Schaeffler, you will play a crucial role in driving business growth through data-driven insights and analytics. Schaeffler, a leading global supplier of bearings and mechatronic components, is seeking an enthusiastic and talented individual to join their Data Science team in India.

The ideal candidate will have a strong foundation in data analysis, machine learning, and statistical modeling, with a passion for working with large datasets to extract actionable insights. As a Junior Data Scientist, you will work closely with cross-functional teams to design, develop, and deploy predictive models that drive business outcomes.

Key Responsibilities:

• Collect, analyze, and interpret large datasets to identify trends, patterns, and correlations, using tools like Python, R, and SQL
• Develop and deploy machine learning models using scikit-learn, TensorFlow, and PyTorch to solve complex business problems
• Collaborate with data engineers to design and implement data pipelines that enable efficient data processing and analysis
• Work with business stakeholders to understand their needs and develop data-driven solutions that meet their requirements
• Develop and maintain dashboards and reports to communicate insights and recommendations to stakeholders
• Stay up-to-date with emerging trends and technologies in data science, artificial intelligence, and machine learning

Requirements:

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field
• 1-3 years of experience in data science, machine learning, or a related field
• Strong programming skills in Python, R, or SQL
• Experience with machine learning libraries like scikit-learn, TensorFlow, and PyTorch
• Familiarity with data visualization tools like Tableau, Power BI, or D3.js
• Strong analytical and problem-solving skills, with the ability to communicate complex ideas to non-technical stakeholders
• Experience working with large datasets and big data technologies like Hadoop, Spark, or NoSQL databases

Nice to Have:

• Experience with deep learning and natural language processing techniques
• Familiarity with cloud-based data platforms like AWS, GCP, or Azure
• Experience with agile development methodologies and version control systems like Git
• Certification in data science, machine learning, or a related field

What We Offer:

• The opportunity to work with a global leader in the automotive and industrial sectors
• A dynamic and supportive work environment that encourages innovation and growth
• Collaborative and cross-functional teams that drive business outcomes
• Professional development opportunities to enhance your skills and expertise
• A comprehensive benefits package that includes health insurance, retirement plans, and paid time off

As a Junior Data Scientist at Schaeffler, you will have the opportunity to work on complex data science projects that drive business growth and innovation. If you are passionate about data analysis, machine learning, and statistical modeling, and have a strong desire to learn and grow, then this is the perfect opportunity for you.

Qualification for Data Scientist - Junior at Schaeffler

Education:

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Engineering, or related fields
• Relevant academic projects or research experience in data science, machine learning, or related areas

Technical Skills:

• Programming skills in languages such as Python, R, or SQL
• Experience with data science tools and technologies like TensorFlow, PyTorch, scikit-learn, or pandas
• Familiarity with data visualization tools like Tableau, Power BI, or D3.js
• Knowledge of operating systems like Windows, Linux, or macOS
• Experience with cloud-based platforms like AWS, Azure, or Google Cloud

Data Science Skills:

• Data preprocessing, wrangling, and feature engineering
• Data modeling, machine learning, and deep learning
• Experience with supervised and unsupervised learning algorithms
• Knowledge of regression, classification, clustering, and dimensionality reduction techniques
• Familiarity with data mining and text mining concepts

Tools and Technologies:

• Experience with big data technologies like Hadoop, Spark, or NoSQL databases
• Familiarity with data warehousing and ETL (Extract, Transform, Load) processes
• Knowledge of data governance, data quality, and data security principles
• Experience with agile development methodologies and version control systems like Git

Soft Skills:

• Excellent problem-solving skills and attention to detail
• Strong communication and interpersonal skills
• Ability to work effectively in a team environment
• Strong business acumen and understanding of industry trends
• Adaptability, flexibility, and willingness to learn

Domain Knowledge:

• Familiarity with the industrial or automotive industry (optional but desirable)
• Knowledge of Schaeffler's products and services (optional but desirable)

Experience:

• 0-3 years of experience in data science, machine learning, or related fields
• Experience working with datasets, data modeling, and machine learning algorithms
• Familiarity with data analysis and data visualization tools

Certifications:

• Relevant certifications in data science, machine learning, or related areas (optional but desirable)
• Certifications from reputable institutions or organizations like Coursera, edX, or Data Science Council of America (DASCA)

Language Skills:

• Fluent in English (written and spoken)
• Hindi or German language skills (optional but desirable)

Schaeffler-specific Requirements:

• Familiarity with Schaeffler's IT infrastructure and systems (optional but desirable)
• Knowledge of Schaeffler's data management and analytics strategy (optional but desirable)

Nice to Have:

• Experience with DevOps tools like Jenkins, Docker, or Kubernetes
• Familiarity with cloud-based data platforms like Snowflake or Google BigQuery
• Knowledge of data storytelling and presentation techniques
• Experience with MLOps and model deployment strategies

What We Offer:

• Opportunity to work with a global leader in the automotive and industrial sectors
• Collaborative and dynamic work environment
• Professional development and growth opportunities
• Comprehensive training and onboarding program
• Flexible working hours and remote work options

As a Data Scientist - Junior at Schaeffler, you will have the opportunity to work on exciting projects, develop your skills, and contribute to the company's success. If you have a passion for data science and are looking for a challenging and rewarding role, this could be the perfect opportunity for you.

• Develop and deploy machine learning models to drive business growth and improve decision-making at Schaeffler, a leading global automotive and industrial supplier.
• Collaborate with cross-functional teams to identify business problems and develop data-driven solutions, leveraging expertise in data analysis, modeling, and visualization.
• Design, build, and maintain large-scale data pipelines to extract insights from various data sources, including structured and unstructured data, using tools like Python, R, SQL, and Tableau.
• Work with junior and senior data scientists to integrate data science solutions into business operations, ensuring seamless execution and scalability.
• Conduct exploratory data analysis to identify trends, correlations, and patterns in complex data sets, using statistical techniques and data visualization tools.
• Develop and maintain dashboards and reports to communicate insights and recommendations to stakeholders, including senior leadership and product managers.
• Stay up-to-date with emerging trends and technologies in data science, including deep learning, natural language processing, and computer vision, and apply them to drive business innovation.
• Work closely with product managers to identify opportunities for data-driven product development and improvement, and collaborate with engineers to integrate data science solutions into product roadmaps.
• Apply expertise in programming languages, including Python, R, and SQL, to develop scalable and efficient data science solutions.
• Utilize data visualization tools, such as Tableau, Power BI, or D3.js, to communicate complex data insights to non-technical stakeholders.
• Develop and maintain large-scale data models, including data warehousing and ETL processes, using tools like AWS, Azure, or Google Cloud.
• Collaborate with data engineers to design and implement data architectures that meet business requirements, including data governance, security, and compliance.
• Apply knowledge of statistical techniques, including regression, clustering, and decision trees, to drive business insights and inform decision-making.
• Work with business stakeholders to identify and prioritize data-driven projects, and develop project plans to deliver solutions that meet business needs.
• Develop and maintain technical documentation of data science solutions, including data models, algorithms, and code, to ensure reproducibility and scalability.
• Participate in knowledge-sharing activities, including blog posts, presentations, and training sessions, to promote data science best practices and expertise across Schaeffler.
• Collaborate with external partners and vendors to leverage emerging technologies and innovative solutions, and apply them to drive business growth and innovation.
• Stay current with industry trends and developments in data science, including advancements in AI, machine learning, and data engineering, and apply them to drive business innovation and growth.
• Work in a fast-paced, dynamic environment, adapting to changing priorities and deadlines, and demonstrating flexibility and resilience in the face of ambiguity and uncertainty.
• Contribute to the development of Schaeffler's data science strategy, including identifying opportunities for innovation and growth, and developing plans to achieve them.
• Develop and maintain relationships with key stakeholders, including business leaders, product managers, and external partners, to drive business growth and innovation through data science.
• Apply expertise in data science to drive business outcomes, including revenue growth, cost reduction, and improved customer satisfaction.
• Participate in the development of data science metrics and KPIs, including metrics to measure the effectiveness of data science solutions and inform business decision-making.
• Stay up-to-date with regulatory requirements and industry standards, including GDPR, HIPAA, and CCPA, and ensure that data science solutions meet compliance and governance requirements.
• Work effectively in a team environment, collaborating with junior and senior data scientists, data engineers, and business stakeholders to drive business growth and innovation through data science.
• Develop and maintain expertise in specific data science tools and technologies, including Python, R, SQL, Tableau, and TensorFlow.
• Apply knowledge of cloud-based technologies, including AWS, Azure, or Google Cloud, to develop scalable and efficient data science solutions.
• Utilize agile methodologies, including Scrum and Kanban, to develop and deploy data science solutions in a fast-paced, dynamic environment.
• Participate in code reviews and ensure that data science solutions meet Schaeffler's coding standards and best practices.
• Develop and maintain a deep understanding of Schaeffler's business operations, including products, services, and markets, and apply this knowledge to drive business growth and innovation through data science.
• Apply expertise in data storytelling to communicate complex data insights to non-technical stakeholders, including senior leadership and product managers.
• Collaborate with external partners and vendors to leverage emerging technologies and innovative solutions, and apply them to drive business growth and innovation at Schaeffler.
• Stay current with industry trends and developments in data science, including advancements in AI, machine learning, and data engineering, and apply them to drive business innovation and growth at Schaeffler.
• Develop and maintain a comprehensive understanding of data science tools and technologies, including data visualization, machine learning, and data engineering.
• Apply expertise in data science to drive business outcomes, including revenue growth, cost reduction, and improved customer satisfaction at Schaeffler.
• Participate in the development of data science metrics and KPIs, including metrics to measure the effectiveness of data science solutions and inform business decision-making at Schaeffler.
• Work effectively in a team environment, collaborating with junior and senior data scientists, data engineers, and business stakeholders to drive business growth and innovation through data science at Schaeffler.
• Develop and maintain expertise in specific data science tools and technologies, including Python, R, SQL, Tableau, and TensorFlow at Schaeffler.
• Apply knowledge of cloud-based technologies, including AWS, Azure, or Google Cloud, to develop scalable and efficient data science solutions at Schaeffler.
• Utilize agile methodologies, including Scrum and Kanban, to develop and deploy data science solutions in a fast-paced, dynamic environment at Schaeffler.
• Participate in code reviews and ensure that data science solutions meet Schaeffler's coding standards and best practices.
• Develop and maintain a deep understanding of Schaeffler's business operations, including products, services, and markets, and apply this knowledge to drive business growth and innovation through data science at Schaeffler India, Pune location.

Selection Process for Junior Data Scientist at Schaeffler

Overview of the Selection Process

• The selection process for Junior Data Scientist at Schaeffler is designed to assess the candidate's technical skills, business acumen, and behavioral competencies.
• The process consists of multiple rounds, each evaluating a specific aspect of the candidate's profile.

Round 1: Online Assessment

• The online assessment is the initial step in the selection process.
• It consists of a 60-minute test with 30 multiple-choice questions, divided into:
  • Technical skills (20 questions): data structures, algorithms, statistics, and data analysis
  • Logical reasoning (5 questions): problem-solving and critical thinking
  • English proficiency (5 questions): grammar, vocabulary, and comprehension
• The test is conducted on a platform that provides a virtual environment for coding and data analysis.

Round 2: Technical Interview

• The technical interview is conducted via video conferencing and lasts for 45-60 minutes.
• The interviewer assesses the candidate's:
  • Technical skills: programming languages (Python, R, SQL), data analysis, machine learning, and data visualization
  • Problem-solving skills: case studies and scenario-based questions
  • Communication skills: ability to explain technical concepts and ideas
• The interviewer may ask questions on:
  • Data preprocessing and feature engineering
  • Model selection and evaluation metrics
  • Data visualization tools (Tableau, Power BI, etc.)

Round 3: Business Case Study Presentation

• The business case study presentation is a 30-minute session where the candidate is given a real-world business problem related to data science.
• The candidate is expected to:
  • Analyze the problem and identify key insights
  • Develop a solution and present it to the interviewer
  • Answer questions and provide recommendations
• The presentation assesses the candidate's:
  • Business acumen: understanding of the industry and business operations
  • Analytical skills: ability to analyze data and derive insights
  • Communication skills: ability to present complex ideas effectively

Round 4: Behavioral Interview

• The behavioral interview is a 45-60 minute session that focuses on the candidate's past experiences and behaviors.
• The interviewer assesses the candidate's:
  • Teamwork and collaboration skills
  • Adaptability and flexibility
  • Problem-solving and decision-making skills
  • Communication and interpersonal skills
• The interviewer may ask questions on:
  • Previous projects and accomplishments
  • Challenges and failures
  • Leadership and teamwork experiences

Round 5: Final Interview with Hiring Manager

• The final interview is a 30-60 minute session with the hiring manager.
• The hiring manager assesses the candidate's:
  • Overall fit for the role and the company
  • Technical and business skills
  • Behavioral competencies
• The interviewer may ask questions on:
  • Long-term career goals and aspirations
  • Expectations and motivations
  • Fit with Schaeffler's culture and values

Tips for Preparation

• Review data science concepts, including machine learning, statistics, and data visualization
• Practice coding in Python, R, and SQL
• Familiarize yourself with data analysis and visualization tools (Tableau, Power BI, etc.)
• Develop a strong understanding of business operations and industry trends
• Prepare examples of past experiences and behaviors that demonstrate teamwork, adaptability, and problem-solving skills
• Practice presenting complex ideas and solutions effectively

Key Skills and Competencies

• Technical skills: programming languages, data analysis, machine learning, and data visualization
• Business acumen: understanding of industry and business operations
• Behavioral competencies: teamwork, adaptability, problem-solving, and communication skills
• Data analysis and interpretation
• Model selection and evaluation metrics
• Data visualization and presentation

Company Culture and Values

• Schaeffler values innovation, teamwork, and customer satisfaction
• The company culture emphasizes collaboration, continuous learning, and employee development
• The Junior Data Scientist role requires a strong passion for data science, business acumen, and excellent communication skills.

Company Overview

• Schaeffler is a leading global supplier of high-precision components and systems for the automotive and industrial sectors.
• Headquartered in Herzogenaurach, Germany, the company has a rich history dating back to 1946 and has established itself as a pioneer in the development and production of innovative technologies.

Work Environment

• Schaeffler's Indian operations are based in Maharashtra, with state-of-the-art manufacturing facilities and a strong research and development presence.
• The company fosters a culture of innovation, collaboration, and continuous learning, providing employees with opportunities to grow and develop their skills.
• Work environment is dynamic, fast-paced, and challenging, with a focus on delivering high-quality products and services.

Job Opportunities

• Schaeffler offers a wide range of job opportunities across various functions, including:
  • Engineering and Development: design, development, and testing of new products and technologies.
  • Production and Manufacturing: production planning, quality control, and supply chain management.
  • Sales and Marketing: sales, marketing, and distribution of products and services.
  • Finance and Administration: accounting, controlling, and human resources.
• The company provides opportunities for both fresh graduates and experienced professionals to join its team.

Employee Benefits

• Schaeffler offers a comprehensive benefits package, including:
  • Competitive salary and bonus structure.
  • Health insurance and medical benefits.
  • Retirement savings plan and pension scheme.
  • Paid time off and vacation leave.
  • Employee assistance programs and counseling services.
• The company also provides opportunities for professional growth and development, including training programs, mentorship, and education assistance.

Diversity and Inclusion

• Schaeffler values diversity and inclusion, promoting a culture of equality and respect.
• The company encourages diversity in its workforce, with a focus on hiring and retaining talented individuals from diverse backgrounds.
• Schaeffler's diversity and inclusion initiatives include:
  • Employee resource groups and networking opportunities.
  • Diversity and inclusion training programs.
  • Flexible work arrangements and work-life balance.

Sustainability and Social Responsibility

• Schaeffler is committed to sustainability and social responsibility, with a focus on reducing its environmental footprint.
• The company has implemented various initiatives to reduce energy consumption, waste, and emissions.
• Schaeffler also supports community development programs and social causes, including education, healthcare, and environmental conservation.

Innovation and Technology

• Schaeffler is a leader in innovation and technology, with a strong focus on research and development.
• The company has developed various innovative products and technologies, including:
  • Electric vehicle components and systems.
  • Autonomous driving technologies.
  • Industry 4.0 solutions and digitalization.
• Schaeffler's innovation and technology initiatives include:
  • Collaborations with startups and technology partners.
  • Investment in research and development facilities.
  • Employee training and development programs.

Leadership and Management

• Schaeffler's leadership team consists of experienced professionals with a strong track record of success.
• The company's management structure is designed to promote transparency, accountability, and employee engagement.
• Schaeffler's leadership and management initiatives include:
  • Leadership development programs and training.
  • Employee feedback and engagement surveys.
  • Performance management and recognition programs.

Global Presence

• Schaeffler has a global presence, with operations in over 30 countries and a workforce of over 80,000 employees.
• The company's global network provides opportunities for international collaboration, knowledge sharing, and career development.
• Schaeffler's global presence includes:
  • Manufacturing facilities and research and development centers.
  • Sales and distribution networks.
  • Partnerships and collaborations with other companies and organizations.