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Causal Inference Machine Learning Postdoctoral Jobs in Florida

Lorven Technologies

Data Scientist

Tampa, FL · On-site

... in Supervised, unsupervised Machine Learning (ML) algorithms, forecasting and inventory ... Statistical Analysis & Experimentation - A/B testing, causal inference, and hypothesis testing to ...

Opendoor

Applied Scientist- Pricing

Miami, FL · On-site

$156K - $335K/yr

Experience with one or more of the following: causal inference, Bayesian modeling, structural ... Experience with machine learning methods broadly, including where deep learning can complement ...

Chewy

Associate Director Product Manager

Plantation, FL

$166K - $265K/yr

In this role, you will own the product roadmap for Pricing Data Science, Machine Learning, and AI ... Experience with experimentation, A/B testing, causal inference, measurement design, or model ...

Lorven technologies

Data Scientist

Tampa, FL · On-site

$130K - $140K/yr

... in Supervised, unsupervised Machine Learning (ML) algorithms, forecasting and inventory ... Statistical Analysis & Experimentation - A/B testing, causal inference, and hypothesis testing to ...

Ucf

Postdoctoral Scholar, Physics

Orlando, FL

Shyam Kattel at the University of Central Florida, has an immediate opening for a postdoctoral ... Expertise with DFT, GC-DFT, and machine learning methods. * Strong oral and written communication ...

Royal Caribbean Group

Data Scientist

Miami, FL · On-site

This position demands top-tier technical expertise in machine learning & generative AI, combined ... Strong understanding of experimental design, statistical testing, and causal inference basics.

Amerilife Group, LLC

Data Scientist

Clearwater, FL · On-site

Technical Requirements Statistics & Machine Learning Required * Strong foundation in statistical ... causal inference * Experience optimizing models for business ROI; exposure to reinforcement ...

AmeriLife Group, LLC

Data Scientist

Clearwater, FL · On-site

Technical Requirements Statistics & Machine Learning Required * Strong foundation in statistical ... causal inference * Experience optimizing models for business ROI; exposure to reinforcement ...

CEI

Senior ML Platform Engineer

Kissimmee, FL

$70 - $80/hr

Partner with computer vision and machine learning teams to deploy and operationalize models * Support inference pipelines and ML workloads running in production * Assist with deployment, monitoring ...

Acclaim

Principal Machine Learning Engineer

Miami, FL · On-site +1

Strong understanding of inference, latency, scaling, monitoring, and reliability * Strong ML background overall (ML Scientist / ML Engineer trajectory) * Strong coding and engineering skills ...

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Causal Inference Machine Learning Postdoctoral information

What is a Causal Inference Machine Learning Postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a Causal Inference Machine Learning Postdoctoral researcher, and why are they important?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by Causal Inference Machine Learning Postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Florida? For Causal Inference Machine Learning Postdoctoral jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Causal Inference Machine Learning Postdoctoral jobs in Florida look for? The top searched job categories for Causal Inference Machine Learning Postdoctoral jobs in Florida are:
What cities in Florida are hiring for Causal Inference Machine Learning Postdoctoral jobs? Cities in Florida with the most Causal Inference Machine Learning Postdoctoral job openings:
Causal Inference Machine Learning Postdoctoral jobs near you
Data Scientist

Data Scientist

Lorven Technologies

Tampa, FL • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Title: Data Scientist
Location: Austin, TX 78757 (or) Tampa, FL 33602 - Remote
Full-Time
As Data Scientist, you will spearhead the end-to-end development of sales forecasting and demand sensing models for CPG portfolios on Databricks (Azure). Work closely with commercial, supply chain, and engineering teams to build ML solutions that improve forecast accuracy, reduce inventory waste, and support revenue growth. Bring deep ML expertise, strong Python engineering skills, and a nuanced understanding of CPG market dynamics - and you are comfortable translating complex model outputs into clear business recommendations.
Skills / Experience:
  • 8+ years in data science or Applied ML roles; 3+ years of experience in Databricks in production
  • 5+ years of experience in Python - Pandas, PySpark, scikit-learn, Azure ML or Azure ecosystem and Databricks experience in production
  • 5+ years of experience in Supervised, unsupervised Machine Learning (ML) algorithms, forecasting and inventory optimization
  • 5+ years of experience in deep learning algorithms applying to solve forecasting, regression and classification problems
  • 3+ years of experience in building ML models in CPG, FMCG, or Retail analytics industry
  • 3+ years of experience in MLflow or equivalent experiment tracking tool
  • Master's or PhD in Statistics, CS, or related field (preferred)

Job / Role Description:
  • Lead end-to-end sales forecasting model development - from data sourcing and feature engineering through model training, validation, and productionisation on Databricks (Azure)
  • Design and maintain forecasting pipelines - at SKU, category, and regional hierarchy levels - incorporating POS data, promotional calendars, seasonality indices, and external signals (macroeconomic, weather)
  • Apply CPG domain knowledge - to model promotional uplift, new product introduction curves, product cannibalization, and retailer sell-in/sell-out dynamics into ML features and targets
  • Operationalise ML models using MLflow on Databricks - manage the model registry, version control experiments, automate retraining schedules, and configure drift monitoring alerts
  • Collaborate with commercial and supply chain teams - to translate forecast outputs into inventory recommendations, production planning inputs, and revenue growth strategies
  • Define and enforce data science best practices - modelling standards, experiment documentation, code review guidelines, and reproducibility requirements across the team
  • Mentor junior data scientists - conduct code reviews, lead knowledge-sharing sessions, support career development, and build a high-performance data science culture
  • Communicate model insights and forecast accuracy - to senior stakeholders through dashboards, executive briefings, and written reports - making complex model behaviour accessible to business audiences
  • Drive continuous model improvement - benchmark new algorithms, evaluate AutoML approaches, and run controlled experiments to improve MAPE, bias, and coverage metrics
  • Partner with data and platform engineers - to ensure feature pipelines on Azure Data Lake / Delta Lake are reliable, scalable, and aligned with model refresh cadence requirements
  • Communicate effectively with internal and customer stakeholders; Strong interpersonal skills to build and maintain productive relationships with team members
  • Problem-Solving and Analytical Thinking; Capability to troubleshoot and resolve issues efficiently
  • Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps
  • Provides regular updates, proactive and due diligent to carry out responsibilities

Expected Outcome / What Success Looks Like
  • Data Scientist is expected to meet customer expectations within accelerated timelines, enabling us to strengthen our capabilities and drive growth in this area
  • Statistical Analysis & Experimentation - A/B testing, causal inference, and hypothesis testing to measure the business impact of model improvements and pricing interventions
  • This role offers the opportunity to lead high-impact data science initiatives that directly shape customer outcomes and gain strong visibility with senior leadership
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About Lorven technologies

Sourced by ZipRecruiter

Lorven Technologies, headquartered in Plainsboro, New Jersey, United States, is a reputable company in the technology industry, specializing in providing effective IT solutions and consulting services. The company's official website, lorventech.com, offers comprehensive insights into its offerings which include but are not limited to software development, IT consulting, project management, and business analysis. Since its inception, Lorven Technologies has been committed to ensuring efficiency and reliability in delivering IT services to its global clientele, establishing itself as a trusted name in the industry.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

2001

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