Levi Strauss is hiring for a fresher entry level Data Scientist I role in India

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.