Posted:3 weeks ago|
Platform:
Remote
Full Time
PLEASE READ BEFORE APPLY:
We are disrupting the supply chain planning industry with our AI-driven demand planning and inventory replenishment software. The total addressable market (TAM) for supply chain management (SCM) software is substantial and growing rapidly. In 2023, the global SCM software market was valued at approximately $28.9 billion and is projected to reach $45.2 billion by 2027, reflecting a compound annual growth rate (CAGR) of around 9.4% during the forecast period.
We specifically target the rapidly growing segment of the supply chain management (SCM) industry: small and medium-sized businesses (SMBs). This focus has become even more pertinent in light of the supply chain disruptions caused by COVID-19. SMBs now have access to technological advantages previously exclusive to large enterprise companies like Walmart, Amazon, Lowe's, and Home Depot, who have invested hundreds of millions into these technologies.
In this role, you will be responsible for designing, implementing, and deploying the next-generation platform tightly integrated with Amazon AWS services such as EMR, Athena, Glue, and Spark. You will develop an ultra-real-time, AI-driven demand planning engine to help our client serve industries that manage perishable items, including food manufacturing, restaurants, grocery stores, pharmaceuticals, and more.
If you are passionate about leveraging machine learning and AI technologies to solve complex supply chain challenges, this is the perfect opportunity for you.
Fast Facts About Our Company:
• Employee Count: 500+, 58 in Engineering (6 in the US and 52 in Pune India)
• Customer Count: 200+
• Revenue: $25.0M in ARR (and growing fast)
• Profitable: Yes
Job Description
We are modernizing our demand forecasting capabilities through an enterprise-grade ML platform. We are seeking a highly skilled Senior Data Scientist / ML Engineer to design and operationalize advanced forecasting solutions at scale. This role blends hands-on machine learning with solid software engineering practices to deliver robust, scalable, and transparent forecasting capabilities.
JOB RESPONSIBILITIES
What You'll Do:
• Design, build, and deploy production-grade forecasting models
• Develop end-to-end machine learning pipelines for data ingestion, feature engineering, model training, and deployment
• Build probabilistic models to quantify forecast uncertainty
• Write clean, modular, object-oriented code following best practices
• Implement MLOps best practices including model versioning, monitoring, and CI/CD
• Work with distributed training frameworks for scalable model development
• Collaborate with cross-functional teams (engineering, product, strategy) to align solutions with business needs
• Work with cloud-based environments (e.g., Databricks, AWS, GCP) for large-scale data processing
EXPERIENCE:
• Experience in demand forecasting or retail/supply chain
• Exposure to containerization (Docker, Kubernetes)
• Familiarity with data orchestration frameworks (Airflow, Prefect)
• Experience with explainable AI frameworks
REQUIRED EXPERIENCE
· 3–6 years of relevant experience in Data Science / ML Engineering
· Strong proficiency in Python and core libraries such as pandas, numpy, scikit-learn
· Hands-on experience with deep learning frameworks (preferably PyTorch)
· Experience with distributed training and large-scale datasets
· Proven ability to build scalable, production-grade ML pipelines
· Familiarity with MLOps practices (CI/CD, monitoring, retraining pipelines)
· Solid understanding of statistical modeling, regression, and time series
· Experience working in cloud environments (Databricks, AWS, GCP)
· Strong software engineering skills with a focus on clean, modular, object-oriented code
· Excellent problem-solving, communication, and collaboration skills
REQUIRED EDUCATION
• MS or BS in CS or related from a top university
Verticalmove, Inc
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