Experience: 2-7 years
Location: Gurgaon (work from office)
About Trademo
Trademo is a Global Supply Chain Intelligence SaaS Company, headquartered in Palo-Alto , CA. Trademo collects public and private data on global trade transactions, sanctioned parties, trade tariffs, ESG and other events using its proprietary algorithms.Trademo analyzes and performs advanced data processing on billions of data points (50Tb +) using technologies like Graph Databases, Vector Databases, ElasticSearch, MongoDB, NLP and Machine Learning (LLMs) to build end-to-end visibility on Global Supply Chains.Trademo’s vision is to build a single truth on global supply chains to help large and small businesses – discover new commerce opportunities, ensure compliance with trade regulations and build operational resilience. World top giants like Amazon, DHL, Unilever, Blueberry and other 150+ enterprise customers are already on our platform.
Trademo is recognized as the most innovative and disruptive startup in the bay area 2022. Trademo is the rarest Indian SAAS startup who secured 100 crs seed funding. Trademo has been founded by Shalabh Singhal who is a third-time tech entrepreneur. He earlier founded Credence, a Data-driven Digital Marketing, CRM Product and Sales Solutions company.
Shalabh is an Alumni of Goldman Sachs, IIT BHU, CFA Institute USA and Stanford GSB SEED.Tech is the DNA of Trademo, 40+ top notch coders engineering folks are building next-generation high-impact products from India to the world. Our team is distributed in 3 verticals:(A). Application Development (Front end – NextJs , ReactJs, Backend- Django, Elasticsearch, MongoDB, GoLang)
(B). Platform & devOps – Terraform (IaC), Kubernetes , CI/CD, etc.
(C). Data Science & Engg – GraphDB, vector databases , LLMs, NLP, Apache Airflow, tensorflow, scikit- learn, MLFlow etc.
Website: www.trademo.com
Location: Gurgaon
Role Description
This is a full-time on-site Lead Data Scientist role based in Gurugram. The Lead Data Scientist will be responsible for overseeing the data science team, implementing and managing Machine Learning, and Artificial Intelligence models, building and implementing statistical models, analyzing large datasets, visualizing data, and communicating results and insights to relevant stakeholders. The role includes mentoring junior data scientists, developing data strategies, and collaborating with cross-functional teams.
What you will be doing at Trademo
As the Lead Data Scientist at Trademo, you will play a pivotal role in shaping the future of supply chain intelligence through the application of cutting-edge AI and ML techniques. Your responsibilities will encompass a wide range of activities, from selecting state-of-the-art ML approaches to deploying and monitoring models via MLOps.
Here’s a breakdown of your key responsibilities:
1. State-of-the-Art ML Approach:
● Champion the adoption of the latest and most advanced ML methodologies, keeping Trademo at the forefront of innovation.
● Evaluate, select, and implement the most suitable ML algorithms to address complex supply chain challenges.
● Oversee the end-to-end ML pipeline, from data preprocessing and model training to deployment and performance monitoring.
2. Problem Solving with AI/ML:
● Collaborate closely with product managers to identify and understand business problems, then apply AI/ML techniques to develop impactful solutions.
● Lead projects related to Name Entity Recognition (NER), Entity Resolution, Deduplication, Classification, Knowledge Graph construction, Reinforcement Learning, and more.
● Develop and refine models that extract valuable insights from large-scale data, providing actionable intelligence for our clients.
3. Team Building and Development:
● Take the lead in hiring and nurturing top-notch data scientists, fostering a culture of excellence and innovation within the data science team.
● Mentor and guide junior data scientists, helping them grow their skills and contribute to our collective success.
● Collaborate cross-functionally with other teams, fostering a collaborative and dynamic working environment.
4. MLOps Deployment and Monitoring:
● Implement best practices in MLOps to streamline model deployment, monitoring, and maintenance.
● Ensure the reliability and scalability of ML systems in production, guaranteeing optimal performance and minimal downtime.
● Continuously monitor model performance and iterate on improvements to maintain model accuracy and relevance.
5. Research and Innovation:
● Stay up-to-date with the latest developments in AI and ML research, and explore how
emerging technologies can be applied to enhance our supply chain intelligence solutions.
● Lead research initiatives, publish findings, and contribute to the broader data science and AI
community.
● Drive innovation and intellectual property development by actively participating in the
creation and filing of patents in the field of machine learning and artificial intelligence,
establishing Trademo as a thought leader in supply chain intelligence technology
● Represent Trademo at leading tech conferences, showcasing our AI/ML capabilities to a
global audience, and forging valuable partnerships and collaborations within the industry.
Skills
● Machine Learning and Deep Learning: Proficiency in developing and deploying machine learning and deep learning models, as well as experience with frameworks like PyTorch, TensorFlow, and scikit-learn.
● Natural Language Processing (NLP): Expertise in NLP techniques, as demonstrated by your use of MiniLM and other NLP models.
● Graph Neural Networks (GNN): Understanding and experience with GNN frameworks like GraphSage, which is crucial for dealing with graph data and building knowledge graphs.
● Python: Mastery of Python for data manipulation, modeling, and scripting.
● Data Manipulation Libraries: Strong proficiency in data manipulation libraries such as Pandas
and NumPy.
● Graph Databases: Knowledge of working with graph databases, which aligns with your use of Vector Databases (Milvus). Familiarity with database systems like Neo4j, JanusGraph, or ArangoDB could be beneficial.
● Reinforcement Learning (RL): Experience with reinforcement learning algorithms, particularly in solving real-world problems.
● MLOps: Familiarity with MLOps practices and tools to ensure smooth deployment, monitoring, and maintenance of machine learning models.
● Distributed Computing: Understanding of distributed computing frameworks and tools such as Apache Spark for handling large-scale data processing.
● Version Control: Proficiency with version control systems like Git for collaborative development.
● Data Visualization: Skills in data visualization tools such as Matplotlib, Seaborn, or Plotly for conveying insights effectively.
● Cloud Computing: Knowledge of cloud platforms like AWS, Azure, or Google Cloud for scalable computing and storage.
● Database Query Languages: Proficiency in NoSQL- MongoDB ,Elasticsearch for data retrieval and manipulation.
● Collaborative Tools: Familiarity with collaboration and project management tools such as Jira, Confluence.
● Continuous Learning: A commitment to staying up-to-date with the latest developments in the field of data science and machine learning through continuous learning and self- improvement.
Qualifications
● Deep understanding of Data Science, Statistics, Applied mathematics,
● Ability to communicate complex data insights and results to non-technical stakeholders
● B.Tech, M.Tech, MSc or PhD in Computer Science, Mathematics, Statistics, or other relevant fields
● Experience in the Supply Chain, Logistics, or Transportation industry is a plus
Please share your resume at poorvi.malhotra@trademo.com
is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the...
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