Position:
- Data Scientist I
Company:
- Levi Strauss & Co.
Location:
- India, Bangalore - Office
Job type:
- Full-time
Job mode:
- On-site
Job requisition id:
- R-0120372
Years of experience:
- 0-3 years
Company Description:
Levi Strauss & Co. (LS&Co.) is a global leader in the apparel industry, recognized for its iconic denim products and progressive work environment. Headquartered in San Francisco, LS&Co. operates in more than 110 countries, designing and selling products under renowned brands like Levi's®, Dockers®, Signature by Levi Strauss & Co.™, and Denizen®. The company embraces innovation and sustainability, striving to lead in both fashion and technology. LS&Co. values diversity and inclusivity, offering a dynamic workplace where creativity, collaboration, and community flourish. With a deep commitment to ethical business practices, LS&Co. is also focused on minimizing its environmental impact and supporting global initiatives for social good. As a pioneer in retail, LS&Co. fosters a forward-thinking culture that encourages employees to bring their best selves to work every day.
Profile Overview:
As a Data Scientist I at Levi Strauss & Co., your role will involve developing and deploying advanced data analytics models that solve real-world business challenges. You will work closely with internal teams to create data-driven insights that shape strategic decisions, improving operational efficiency and customer experiences. You will leverage cutting-edge technologies such as machine learning and artificial intelligence to deliver impactful solutions using both structured and unstructured data from a wide range of sources. In this role, you will collaborate with cross-functional teams, including technical experts and business stakeholders, to drive innovation and enhance the company’s analytics capabilities. A strong focus on teamwork, communication, and business understanding is essential for success. The role demands a proactive approach to problem-solving, a keen interest in continuous learning, and a passion for driving data-based innovation.
Duties and Responsibilities:
Developing Analytical Solutions:
- Create and implement analytical solutions and production-ready models.
- Address real business challenges by considering both business needs and the current technology landscape.
- Develop models that drive business value by leveraging internal and external data sets.
Applying Advanced Analytics:
- Use advanced analytics techniques, such as machine learning and artificial intelligence, to extract business value from various data sources.
- Employ cloud-based "Big Data" technologies to process and analyze large datasets.
- Continuously innovate and experiment with new algorithms and data processing techniques to optimize business outcomes.
Translating Data into Insights:
- Translate complex datasets and methodologies into actionable insights and recommendations.
- Ensure that insights are operationally feasible and aligned with the company’s strategic goals.
- Communicate data findings in a clear and concise manner to both technical and non-technical audiences, ensuring alignment and understanding.
Communication and Collaboration:
- Present data insights both verbally and visually, ensuring that the information is accessible and engaging to all stakeholders.
- Foster collaboration with technical and non-technical teams to gain buy-in on data-driven solutions.
- Work cross-functionally to build understanding, engagement, and consensus around data insights and initiatives.
Innovation and Trend Analysis:
- Identify emerging trends and opportunities for innovation within the data science domain.
- Explore new technologies, methods, and processes to enhance how data is used across the organization.
- Lead initiatives to refine and improve current data practices, focusing on efficiency and effectiveness.
Documentation and Knowledge Sharing:
- Document all code and methodologies used in data projects to ensure reproducibility and future reference.
- Actively contribute to the company’s data science community by sharing best practices and re-using proven techniques.
- Engage in continuous learning and knowledge exchange to stay current with the latest advancements in data science.
Team Collaboration and Culture:
- Work as a proactive and empathetic team player, embodying Levi Strauss & Co.’s core values.
- Foster a collaborative environment where diverse ideas and perspectives are encouraged and valued.
- Engage with colleagues across different departments and backgrounds to drive collective success.
Qualifications:
Required Skills and Education:
Advanced Degree:
- An Advanced degree in Mathematics, Physics, Computer Science, Engineering, Statistics, or a related discipline is required.
Experience:
- Proven experience in building models and developing algorithms.
- A track record of leveraging data science to create meaningful business impacts.
Programming Expertise:
- Strong proficiency in SQL and Python is essential.
- Knowledge of additional programming languages such as R, Java, C++, or other open-source languages is a plus.
Statistical Modeling Expertise:
- Expertise in multivariate statistical modeling techniques such as clustering, regression analysis, principal components analysis (PCA), and time-series forecasting.
- Experience with machine learning algorithms such as Random Forest, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), boosting, and bagging.
Cloud Computing:
- Experience working with cloud platforms such as AWS, Google Cloud Platform (GCP), or equivalent on-premise platforms.
- Understanding of cloud-based data processing and storage technologies to efficiently handle large datasets.
Project Management:
- Ability to coordinate multiple deliverables, tasks, and dependencies across different stakeholders and business units simultaneously.
Desirable Skills:
Deep Learning:
- Familiarity with neural networks and deep learning frameworks such as TensorFlow is highly desirable.
Data Visualization:
- Experience using data visualization tools like D3.js, Tableau, R Shiny, or Looker is a plus.
Big Data Processing:
- Proficiency in data processing frameworks such as Spark or MapReduce is a valuable asset.
Agile Methodology:
- Experience working in an agile development environment, with a focus on continuous improvement and rapid iteration.
Industry Experience:
- Prior experience in retail or the FMCG (Fast-Moving Consumer Goods) sector is advantageous, especially in leveraging data to drive business performance.
Additional Info:
Employee Expectations:
- Levi Strauss & Co. values a culture of innovation, collaboration, and respect. Employees are expected to uphold the company’s values in all their interactions.
- As part of the data science team, you will be expected to stay current on emerging trends in data analytics and AI.
- The role requires a high degree of adaptability, as new challenges and projects will arise regularly.
Benefits:
- Comprehensive Health Coverage: LS&Co. offers a competitive benefits package that includes health insurance for employees and their families.
- Learning and Development: Employees have access to various learning opportunities, including training programs, workshops, and conferences related to data science and analytics.
- Work-Life Balance: The company promotes a healthy work-life balance, providing flexible work schedules when possible to accommodate personal needs.
- Career Growth: Levi Strauss & Co. is committed to supporting the career development of its employees, offering mentorship, career coaching, and leadership programs.
Diversity and Inclusion:
- LS&Co. is an equal opportunity employer and prides itself on fostering an inclusive environment where everyone can thrive. The company is committed to building a workforce that reflects the diversity of the communities it serves.
- Employees are encouraged to participate in the company’s diversity initiatives, which include employee resource groups, mentorship programs, and community outreach.
Application Process:
- Candidates should apply through the Levi Strauss & Co. careers portal or, for current employees, via their Workday account.
- The recruitment process typically involves multiple stages, including an initial screening, technical assessments, and interviews with key stakeholders.
- Applicants are encouraged to showcase their ability to solve complex problems, communicate insights effectively, and demonstrate their passion for leveraging data to drive business success.
Please click here to apply.

