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Tiger Analytics

Senior Data Scientist (Supply Chain)

Reposted 5 Days Ago
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Remote
Hiring Remotely in Canada
Expert/Leader
Remote
Hiring Remotely in Canada
Expert/Leader
The Senior Data Scientist will develop advanced analytical models for supply chain optimization using Python, PySpark, and graph theory, collaborating with various teams to deliver insights and solutions.
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Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

As a Senior Data Scientist with strong expertise in graph theory and advanced data processing to join our Supply Chain Analytics team. The ideal candidate will have hands-on experience leveraging Python, PySpark, and graph-based approaches (preferably with NetworkX) to solve complex business problems in supply chain optimization.. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Key Responsibilities

  • Collaborate with business partners to develop innovative solutions to meet objectives utilizing cutting edge techniques and tools.
  • Design and implement graph-based models to analyze, optimize, and improve supply chain networks.
  • Apply advanced data science techniques to identify patterns, inefficiencies, and bottlenecks across logistics and operations.
  • Build scalable data pipelines and analytical models using PySpark for large-scale supply chain datasets.
  • Develop predictive and prescriptive models to support decision-making in areas such as demand forecasting, routing, and inventory management.
  • Collaborate with cross-functional teams including operations, product, and engineering to translate business challenges into analytical solutions.
  • Communicate insights and recommendations clearly to stakeholders through data storytelling, visualizations, and presentations.
  • Share your passion for Data Science with the broader enterprise community; identify and develop long-term processes, frameworks, tools, methods and standards.
  • Collaborate, coach, and learn with a growing team of experienced Data Scientists.
  • Stay connected with external sources of ideas through conferences and community engagements

Requirements
  • 8+ years of professional experience in Data Science, Analytics, or related roles.
  • Proven expertise in Graph Theory applications; hands-on experience with the NetworkX package strongly preferred.
  • Strong programming skills in Python with demonstrated use of scientific computing libraries (NumPy, Pandas, SciPy, scikit-learn, etc.).
  • Experience with PySpark for large-scale data processing and analytics.
  • Practical exposure to supply chain domain problems such as logistics, distribution networks, or demand planning.
  • Strong analytical, problem-solving, and communication skills.
  • Experience developing models from inception to deployment

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

Top Skills

Networkx
Numpy
Pandas
Pyspark
Python
Scikit-Learn
Scipy

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