Position: Data Scientist - II
Company: Swiggy
Location: India
Job Type: Full-time
Job Mode: Remote (with quarterly meetups)
Job Requisition ID: NA
Years of Experience: 3 to 5 years
Company Description
- Industry: Software Development
- Employee Range: 1,001-5,000
- Mission: Swiggy aims to revolutionize the food delivery industry by leveraging technology to ensure seamless logistics and customer satisfaction.
- Core Values:
- Innovation: Continuously pushing the boundaries of what's possible in food delivery.
- Customer Focus: Ensuring the highest levels of customer service and satisfaction.
- Collaboration: Fostering a team-oriented environment where every member contributes to the company's success.
- Integrity: Maintaining transparency and honesty in all business practices.
Profile Overview
- Role: As a Data Scientist II, you will enhance Swiggy’s logistics operations through advanced data science techniques.
- Responsibilities:
- Logistics Optimization: Work with the logistics team to optimize Assignment and Batching processes.
- Machine Learning Models: Develop and deploy models to improve logistics efficiency and accuracy.
- Data Analysis: Conduct data analysis and modeling to identify opportunities for optimization.
- Cross-functional Collaboration: Work with software developers and product managers to integrate data-driven solutions.
- Project Ownership: Manage projects from inception to delivery, ensuring quality and impact.
- Continuous Learning: Stay updated on advancements in machine learning and logistics optimization.
Qualifications
- Education: Bachelor’s degree or higher in Applied Mathematics, Statistics, Computer Science, or a related field.
- Experience:
- 3 to 5 years in industry or research lab settings.
- Proven track record in developing and deploying machine learning data products.
- Technical Skills:
- Proficiency in Python.
- Strong expertise in machine learning algorithms and statistical methods.
- Experience with Spark (preferred).
- Knowledge of deep learning (preferred).
- Soft Skills:
- Excellent communication skills.
- Strong collaboration abilities.
- Ability to work effectively in a team environment.
- Preferred Background:
- Experience in startup or product-based consumer/internet companies.
Any Additional Info
- Work Environment:
- Remote work throughout the year with quarterly meetups.
- Collaborative and supportive culture.
- Benefits:
- Competitive compensation package.
- Opportunities for professional growth and development.
- Involvement in impactful projects within the logistics domain.
- Application Encouragement: If you are passionate about data science and logistics optimization, this role is an excellent opportunity to apply your skills and make a significant impact.
Detailed Job Description
Key Responsibilities
Logistics Optimization
- Assignment and Batching:
- Collaborate with the logistics team to streamline assignment and batching processes.
- Utilize advanced mathematical techniques to enhance efficiency.
- Implement changes that lead to better resource allocation and time management.
Machine Learning Models
- Development:
- Create and refine machine learning models aimed at improving logistics.
- Ensure models are scalable and can handle large datasets.
- Deployment:
- Implement models into existing systems with minimal disruption.
- Monitor performance and make adjustments as necessary.
Data Analysis and Modeling
- Opportunity Identification:
- Analyze data to uncover areas for optimization.
- Propose solutions based on data-driven insights.
- Automation:
- Develop models to automate routine processes.
- Increase accuracy and efficiency through automation.
Cross-functional Collaboration
- Integration:
- Work with software developers to embed data-driven solutions into Swiggy’s systems.
- Partner with product managers to align data projects with business goals.
- Teamwork:
- Foster a collaborative environment.
- Share knowledge and insights with team members.
Project Ownership
- Management:
- Lead projects from start to finish.
- Ensure timely delivery of high-quality results.
- Impact:
- Focus on delivering results that significantly improve logistics operations.
- Measure and report on project outcomes.
Continuous Learning
- Advancements:
- Stay informed on the latest machine learning techniques.
- Apply new methods to enhance logistics optimization.
- Professional Development:
- Participate in workshops and conferences.
- Share new knowledge with the team.
Qualifications
Educational Background
- Degree:
- Bachelor's degree or higher in Applied Mathematics, Statistics, Computer Science, or related field.
- Preferred Fields:
- Specializations in areas relevant to data science and machine learning.
Professional Experience
- Industry Experience:
- 3 to 5 years of hands-on experience in industry or research settings.
- Experience in logistics or related fields is a plus.
- Research Experience:
- Prior work in research labs can be advantageous.
Technical Proficiency
- Programming:
- Advanced skills in Python.
- Machine Learning:
- In-depth knowledge of algorithms and statistical methods.
- Experience with Spark is beneficial.
- Deep Learning:
- Familiarity with deep learning techniques is preferred.
Soft Skills
- Communication:
- Ability to articulate complex ideas clearly.
- Effective in both written and verbal communication.
- Collaboration:
- Proven ability to work well within a team.
- Experience in cross-functional team settings.
Preferred Background
- Industry Experience:
- Work experience in startups or consumer-focused internet companies.
- Product Development:
- Experience in developing and shipping ML data products.
Why Join Us?
Work Environment
- Remote Work:
- Employees can work remotely all year, with quarterly meetups.
- Culture:
- Supportive and collaborative environment.
Please click here to apply.
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