Tiger Analytics
Lead Data Scientist
Tiger Analytics - Houston, Texas, United States, 77246
Work at Tiger Analytics
Overview
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Overview
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 Data Scientist, you will apply strong expertise through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. 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. Develop, test, and deploy data science solutions using Python, SQL, and PySpark on enterprise platforms such as Databricks. Collaborate with data scientists to translate models into production-ready code. Implement CI/CD pipelines and manage code repositories using GitHub Enterprise. Design and optimize mathematical programming and machine learning models for real-world applications like Incentive elasticity model. Expereince implementing scenario simulation algorithms. Work independently to break down complex problems into actionable development tasks. Ensure code quality, scalability, and maintainability in a production environment. Contribute to sprint planning, documentation, and cross-functional collaboration. 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 experience working as a Data Scientist Hands-on experience with enterprise data science solutions ,
preferably in retail, inventory management, or operations research. Proficiency in
Python, SQL, and PySpark. Experience with
Databricks or similar enterprise cloud environments. Experience with
production-level coding and deployment practices. Familiarity with
basic machine learning techniques and mathematical optimization methods . Proficient in
data science libraries and ML pipelines
such as; NumPy, SciPy, scikit-learn, MLlib, PyTorch, TensorFlow. Self-starter with an
ownership mindset
and the ability to
work with minimal supervision .
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.
As a Data Scientist, you will apply strong expertise through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. 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. Develop, test, and deploy data science solutions using Python, SQL, and PySpark on enterprise platforms such as Databricks. Collaborate with data scientists to translate models into production-ready code. Implement CI/CD pipelines and manage code repositories using GitHub Enterprise. Design and optimize mathematical programming and machine learning models for real-world applications like Incentive elasticity model. Expereince implementing scenario simulation algorithms. Work independently to break down complex problems into actionable development tasks. Ensure code quality, scalability, and maintainability in a production environment. Contribute to sprint planning, documentation, and cross-functional collaboration. 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 experience working as a Data Scientist Hands-on experience with enterprise data science solutions ,
preferably in retail, inventory management, or operations research. Proficiency in
Python, SQL, and PySpark. Experience with
Databricks or similar enterprise cloud environments. Experience with
production-level coding and deployment practices. Familiarity with
basic machine learning techniques and mathematical optimization methods . Proficient in
data science libraries and ML pipelines
such as; NumPy, SciPy, scikit-learn, MLlib, PyTorch, TensorFlow. Self-starter with an
ownership mindset
and the ability to
work with minimal supervision .
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.