Flex Sr Data Scientist United States, Texas, Austin 168525674
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Reporting to thethe,will be in charge ofanalyzing, and interpreting large datasets using statistical methods, developing machine learning, predictive/AI models & algorithms to extract meaningful insights, ultimately providing actionable recommendations to businesses to inform strategic decisions and solve complex problems; their key responsibilities include data collection, cleaning, exploration, model building, data visualization, and communicating findings to stakeholders.
What a typical day looks like:
Use various analytical techniques including visualization, statistical methods, machine learning/AI to create scalable solutions for business problems.
Translate business problems and questions into specific quantitative questions to be answered w/ available data using robust methodologies. In many cases, the data collection at scale will be part of the task and may involve co-work with software development team.
Coordinate and perform testing on data quality and solutions.
Analyze and extract relevant information from big data to help automate and optimize key processes.
Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
Research and implement applicable machine learning and statisticalmodels/algorithms/approaches.
Make business recommendations (e.g. cost-benefit, forecasting, experiment analysis) with effective presentations of findings to stakeholders through visual displays of quantitative information.
Have working knowledge of developing, implementing and/or connecting to API’s
Build scalable prototype analytics solutions.
Work closely with softwaredevelopment/engineeringteams to build model implementations and integrate successful models and algorithms in production systems at scale.
Have some experience with AWS. Azure, LLM, GenAI tools
The experience we’re looking to add to our team,
Master’s Degree + 2-4 years of experience (OR) PhD + 0-2 years of experience
Degrees can be in Engineering, Mathematics, Data Science, Operations Research, Statistics
Completion of reputable online courses in data science, statistics, programming will be considered as a substitute for educational requirements from traditional universities.
Knowledge of analytical techniques including visualization, statistical methods, building machine learning/AI models
Proficiency in languages like Python, R, SQL for data manipulation and analysis
Knowledge of supervised and unsupervised learning algorithms, including regression, classification, and clustering
Collaborate with product design, software, engineering, and business teams to develop an understanding of needs.
Define standards for data completeness and accuracy for specific use cases.
Build scalable prototype analytics solutions.
Ability to effectively communicate complex technical concepts to non-technical audiences.
Work closely with softwaredevelopment/engineeringteams to build model implementations and integrate successful models and algorithms in production systems at scale.
Create, deploy, connect to API’s.
Make business recommendations (e.g. cost-benefit, forecasting, experiment analysis) with effective presentations of findings to stakeholders.
Can summarize analytics findings in both short form(ppt) and long form (detailed write-up in word/pdf) formats for various consumers and stakeholders including executive management.
Ability to communicate clearly in both oral, written form with teammates and colleagues.
Here are a few of our preferred experiences:
Have some experience with AWS, Azure, LLM’s, GenAI tools
Project ownership/management experience
Knowledge and experience in manufacturing and/or supply chain
What you'll receive for the great work you provide:
- Full range of medical, dental, and vision plans
- Life Insurance
- Short-term and Long-term Disability
- Matching 401(k) Contributions
- Vacation and Paid Sick Time
- Tuition Reimbursement
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