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Data Scientist Forecasting Remote Jobs in Michigan

CSAA

Perform complex data analysis for Commercial Claims aligned to business and portfolio objectives ... Bachelor's degree in mathematics, business, statistics, economics, computer science or equivalent ...

Clarivate

Global Strategic Account Director

Ann Arbor, MI · Remote

$153K - $192K/yr

Maintain accurate pipeline, forecasting, and CRM data * Stay current on industry trends Success ... This is a full-time position Remote, primarily working core business hours in your time zone, with ...

micro1 AI

Cheminformatics Specialist - Remote

Detroit, MI · On-site +1

$90 - $120/hr

Remote micro1 is engaging Computational Biology Experts to contribute their advanced scientific ... Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

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Data Scientist Forecasting Remote information

What does a data scientist specializing in forecasting do when working remotely?

A Data Scientist in Forecasting working remotely uses statistical models, machine learning algorithms, and large datasets to predict future trends or outcomes for a business. Their tasks often include gathering and cleaning data, building predictive models, evaluating their accuracy, and communicating findings to stakeholders. Remote data scientists collaborate with teams through virtual meetings and cloud-based tools, ensuring their forecasts support business decisions. The remote aspect offers flexibility but requires strong communication and self-management skills.

How does a remote data scientist specializing in forecasting typically collaborate with cross-functional teams?

Remote Data Scientists in forecasting roles regularly collaborate with product managers, engineers, and business analysts through virtual meetings, shared dashboards, and project management tools. They are often responsible for presenting forecast results, discussing model assumptions, and incorporating stakeholder feedback to refine predictions. Effective communication and documentation are crucial, as team members may operate across different time zones. This collaborative environment helps ensure that forecasting models align with business goals and can be effectively integrated into decision-making processes.

What are the key skills and qualifications needed to thrive as a data scientist specializing in forecasting in a remote role?

To thrive as a Data Scientist specializing in Forecasting, you need a strong background in statistics, mathematics, and machine learning, usually supported by a degree in a quantitative field. Proficiency with programming languages such as Python or R, experience with forecasting libraries (like Prophet or ARIMA), and familiarity with cloud-based data platforms are typically required. Excellent communication, problem-solving abilities, and self-motivation are crucial soft skills for collaborating remotely and translating complex findings into actionable insights. These skills and qualities are vital for building accurate predictive models and ensuring effective decision-making in distributed teams.

What is the difference between Data Scientist Forecasting Remote vs Data Analyst Forecasting Remote?

AspectData Scientist Forecasting RemoteData Analyst Forecasting Remote
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related field; often some experience with machine learningBachelor's in Data Analysis, Statistics, or related field; typically less emphasis on advanced modeling
Work EnvironmentCollaborative teams, often in tech or finance industries; remote work commonBusiness units, marketing, or finance teams; remote options widely available
Employer & Industry UsageTech companies, finance, e-commerce; focus on predictive modeling and forecastingRetail, marketing, finance; focus on reporting and trend analysis

Data Scientist Forecasting Remote roles focus on advanced predictive modeling and machine learning, requiring higher technical skills and credentials. Data Analysts Forecasting Remote positions emphasize data reporting and trend analysis with less emphasis on complex modeling. Both roles are often remote and serve similar industries, but differ in technical depth and responsibilities.

What are the most commonly searched types of Data Scientist Forecasting jobs in Michigan?

The most popular types of Data Scientist Forecasting jobs in Michigan are:

What are popular job titles related to Data Scientist Forecasting Remote jobs in Michigan?

For Data Scientist Forecasting Remote jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Data Scientist Forecasting Remote jobs in Michigan look for?

The top searched job categories for Data Scientist Forecasting Remote jobs in Michigan are:

Data Scientist Forecasting Remote jobs near you

AI Machine Learning Engineer (AI / ML: Python / Go)

Benzinga

Detroit, MI • On-site, Remote

Full-time

Re-posted yesterday

Job description

About Benzinga
Benzinga is a fast-growing financial media and data technology company reshaping how investors access information. We combine artificial intelligence, machine learning, and real-time data pipelines to surface insights before they hit the mainstream. Our platforms deliver structured news, sentiment analytics, and financial data APIs used by leading banks, fintechs, and AI companies worldwide.
We're seeking a highly motivated AI / Machine Learning Engineer who thrives at the intersection of data science and backend engineering - someone who can take a model from notebook to production, and architect intelligent systems in Go and Python that scale to millions of requests.
The ideal candidate is a self-starter who independently identifies opportunities, experiments with new approaches, and ships production-ready solutions without constant direction.
Key Responsibilities
AI / Machine Learning
  • Research, design, and deploy machine learning models across NLP, time-series forecasting, and event detection domains.
  • Build LLM-driven systems (e.g. summarization, RAG pipelines, embedding search) optimized for financial news and quantitative data.
  • Develop model serving APIs and scalable inference layers using Go or Python.
  • Implement model monitoring, drift detection, and continuous retraining pipelines.
  • Work with financial text (earnings call transcripts, filings, news) to extract structured insights.
  • Collaborate with data engineers to build training datasets, feature stores, and embedding databases.

Backend & Infrastructure
  • Develop and maintain high-performance Python or Go microservices that integrate with AI systems and Go data APIs.
  • Design and optimize real-time inference pipelines on AWS, leveraging ECS/EKS, S3, and Lambda.
  • Ensure low-latency, fault-tolerant, and scalable delivery of AI-powered data.
  • Implement CI/CD for ML workflows, including containerization, automated deployment, and versioning.
  • Partner with DevOps to manage cloud infrastructure and ensure robust observability for AI workloads.

Requirement for applying:
  • During your screening you will be required to submit a Loom video walkthrough of your most exceptional product, share relevant code/repo links, and describe the biggest challenge you faced building it.

Required Qualification
  • 4+ years of experience in AI/ML or data engineering roles, with a proven track record of deploying ML models in production.
  • Computer science degree (Bachelor minimum)
  • Deep proficiency in Python (data, ML) and Go (backend, microservices).
  • Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or Hugging Face.
  • Experience with transformer architectures, embeddings, or fine-tuning LLMs.
  • Strong understanding of data pipelines, feature extraction, and model lifecycle management.
  • Familiarity with Docker, Kubernetes, and AWS (EKS, S3, Lambda, EC2).
  • Excellent problem-solving skills and ability to work independently in a distributed environment.

Preferred Skills / Experience
  • Startup experience.
  • Financial services or fintech background
  • Experience building LLM-powered APIs or retrieval-augmented generation (RAG) systems.
  • Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, OpenSearch kNN).
  • Experience with Kafka, LangChain, or data streaming architectures.
  • Familiarity with financial data systems, real-time analytics, or news NLP.
  • Exposure to MLOps tools (MLflow, BentoML, SageMaker, Airflow, etc.).
  • Contributions to open-source ML or Go projects are a strong plus.

Tech Stack
  • Languages: Python, Go
  • ML Frameworks: PyTorch, TensorFlow, Hugging Face, LangChain
  • Cloud: AWS (EKS, ECS, S3, Lambda, EC2, IAM)
  • Containers & Orchestration: Docker, Kubernetes
  • Data & Streaming: Kafka, Postgres, OpenSearch
  • CI/CD: GitHub Actions, GitLab CI
  • Monitoring: Datadog, Prometheus, Grafana
  • Version Control: Git (Gitlab / Github)

Why Join Benzinga
  • Build and ship production AI systems that shape how financial markets understand information.
  • Operate with full creative freedom - explore, experiment, and execute your ideas end-to-end.
  • Work with a lean, highly technical team where initiative and ownership are celebrated.
  • Fully remote, high-trust environment that rewards curiosity, speed, and execution.
Benzinga logo

About Benzinga

Sourced by ZipRecruiter

Benzinga is a full-service news and media company with three main areas of expertise: real-time news, actionable trading ideas and insightful commentary. We offer coverage of all aspects of the financial market including corporate, economic and political content. With strong connections in and around the market, we strive to provide high quality and relevant news for the real-time environment that defines today's world.

Industry

Video and audio streaming services

Company size

11 - 50 Employees

Headquarters location

Detroit, MI, US

Year founded

2010

Social media

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