Indus Valley
Plano, TX (Hybrid)
Top Must Have's: Tableau Python SQL (very strong)
Min 9+ yrs experience
JD: 9 to 13 years of experience to join our team. The ideal candidate will have expertise in EDA, Statistics, Data Science, R Statistical Package, Python, and SQL. This hybrid role requires a strong analytical mindset and the ability to manage complex geospatial projects. The position offers a day shift with no travel requirements.
Experience : 9 - 13 years
Responsibilities:
Analyze large datasets to identify trends, perform outlier detection, and generate actionable insights. Conduct advanced statistical analyses, including regression modeling, hypothesis testing, and exploratory data analysis, to address business questions. Develop compelling narratives from data insights, articulating business implications, opportunities, and next steps. Collaborate with cross-functional teams to define key business questions and provide solutions through data-driven approaches. Create and optimize SQL queries to extract and manipulate data efficiently. Use Python or R for advanced data manipulation and statistical modeling. Design, implement, and analyze A/B tests and other experimentation methodologies to measure impact. Communicate findings effectively to both technical and non-technical stakeholders through visualizations and presentations. Proficiency in SQL and either Python or R. Strong statistical foundation, with experience in regression, outlier detection, and hypothesis testing. Lead the development and implementation of geospatial data analysis projects - Oversee the collection, processing, and analysis of geospatial data using EDA techniques - Provide statistical analysis and interpretation of geospatial data to support decision-making - Utilize Data Science methodologies to uncover patterns and insights from geospatial datasets - Implement and manage R Statistical Package for advanced geospatial data analysis - Develop and maintain Python scripts for geospatial data processing and analysis - Design and execute SQL queries to extract and manipulate geospatial data from databases - Collaborate with cross-functional teams to integrate geospatial data into broader business strategies - Ensure the accuracy and integrity of geospatial data through rigorous quality control processes - Create and present detailed reports and visualizations of geospatial data findings - Stay updated with the latest advancements in geospatial technologies and methodologies - Mentor and guide junior team members in geospatial data analysis techniques - Contribute to the continuous improvement of geospatial data analysis processes and tools
Qualifications: Must have strong experience in Exploratory Data Analysis (EDA) - Must have expertise in statistical analysis and interpretation - Must be proficient in Data Science methodologies and techniques - Must have advanced knowledge of R Statistical Package - Must be skilled in Python programming for data analysis - Must have experience with SQL for data extraction and manipulation - Nice to have experience in integrating geospatial data into business strategies - Nice to have experience in mentoring and guiding junior team members - Nice to have experience in creating detailed reports and visualizations - Nice to have experience in quality control processes for data accuracy - Nice to have experience in staying updated with geospatial technologies - Nice to have experience in contributing to process improvement - Nice to have experience in collaborating with cross -functional teams.
Top Must Have's: Tableau Python SQL (very strong)
Min 9+ yrs experience
JD: 9 to 13 years of experience to join our team. The ideal candidate will have expertise in EDA, Statistics, Data Science, R Statistical Package, Python, and SQL. This hybrid role requires a strong analytical mindset and the ability to manage complex geospatial projects. The position offers a day shift with no travel requirements.
Experience : 9 - 13 years
Responsibilities:
Analyze large datasets to identify trends, perform outlier detection, and generate actionable insights. Conduct advanced statistical analyses, including regression modeling, hypothesis testing, and exploratory data analysis, to address business questions. Develop compelling narratives from data insights, articulating business implications, opportunities, and next steps. Collaborate with cross-functional teams to define key business questions and provide solutions through data-driven approaches. Create and optimize SQL queries to extract and manipulate data efficiently. Use Python or R for advanced data manipulation and statistical modeling. Design, implement, and analyze A/B tests and other experimentation methodologies to measure impact. Communicate findings effectively to both technical and non-technical stakeholders through visualizations and presentations. Proficiency in SQL and either Python or R. Strong statistical foundation, with experience in regression, outlier detection, and hypothesis testing. Lead the development and implementation of geospatial data analysis projects - Oversee the collection, processing, and analysis of geospatial data using EDA techniques - Provide statistical analysis and interpretation of geospatial data to support decision-making - Utilize Data Science methodologies to uncover patterns and insights from geospatial datasets - Implement and manage R Statistical Package for advanced geospatial data analysis - Develop and maintain Python scripts for geospatial data processing and analysis - Design and execute SQL queries to extract and manipulate geospatial data from databases - Collaborate with cross-functional teams to integrate geospatial data into broader business strategies - Ensure the accuracy and integrity of geospatial data through rigorous quality control processes - Create and present detailed reports and visualizations of geospatial data findings - Stay updated with the latest advancements in geospatial technologies and methodologies - Mentor and guide junior team members in geospatial data analysis techniques - Contribute to the continuous improvement of geospatial data analysis processes and tools
Qualifications: Must have strong experience in Exploratory Data Analysis (EDA) - Must have expertise in statistical analysis and interpretation - Must be proficient in Data Science methodologies and techniques - Must have advanced knowledge of R Statistical Package - Must be skilled in Python programming for data analysis - Must have experience with SQL for data extraction and manipulation - Nice to have experience in integrating geospatial data into business strategies - Nice to have experience in mentoring and guiding junior team members - Nice to have experience in creating detailed reports and visualizations - Nice to have experience in quality control processes for data accuracy - Nice to have experience in staying updated with geospatial technologies - Nice to have experience in contributing to process improvement - Nice to have experience in collaborating with cross -functional teams.