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Junior Data Science Neuroscience Jobs in Arizona

USAA

Data Scientist Senior

Phoenix, AZ

Serves as a mentor to junior data scientists in modeling, analytics, and computer science tasks. * Participates in internal communities that drive the maintenance and transformation of data science ...

New

My3Tech Inc

Junior Data Analysts

Phoenix, AZ · On-site

Charlotte, NC | Dallas, TX | Malvern, PA | Phoenix, AZ -> 3 days on site mandatory Duration: 6 month + Contract to Hire Role focuses on Data Analytics side, a Data Scientist won't translate well or ...

Syntricate Technologies

Data Engineer /Data tester

Tempe, AZ · On-site

$111.40K - $133.80K/yr

Position- Data Engineer /Data tester (either jr. Data Tester or Jr. Data engineer both will work ... Bachelor's degree in Computer Science, Information Systems, Engineering, Technology, or related ...

SynergisticIT

Junior NLP Analyst

Gilbert, AZ · On-site

... Data analysts/ Data Scientists, Machine Learning engineers. Who Should Apply Recent Computer ... if its Junior or entry level position the additional skills and Project work with hands on ...

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Junior Data Science Neuroscience information

What are the key skills and qualifications needed to thrive as a Junior Data Science Neuroscience professional, and why are they important?

A Junior Data Science Neuroscience professional should have a solid background in neuroscience or a related field, combined with proficiency in statistics, data analysis, and programming (typically Python or R). Experience with data visualization tools, machine learning libraries, and familiarity with neuroimaging software (such as SPM, FSL, or AFNI) are highly valuable. Strong analytical thinking, attention to detail, and effective communication skills help in interpreting complex datasets and collaborating across interdisciplinary teams. These skills are essential for extracting meaningful insights from neurological data and advancing research or clinical applications.

What types of projects and collaborations can a Junior Data Scientist expect in a neuroscience research team?

As a Junior Data Scientist in a neuroscience setting, you will typically work on projects that involve processing and analyzing large datasets, such as brain imaging or neural signal recordings. You can expect to collaborate closely with neuroscientists, clinicians, and senior data scientists to interpret results and contribute to experimental design. Your daily tasks may include data cleaning, statistical analysis, and developing machine learning models to uncover patterns related to brain function or disease. This role often offers excellent opportunities for learning and mentorship, as well as potential for growth into specialized or leadership positions as you gain experience.

What is a Junior Data Science Neuroscience role?

A Junior Data Science Neuroscience role involves applying data science techniques to analyze and interpret complex neuroscience data. Professionals in this position typically work with large datasets from brain imaging, electrophysiology, or behavioral experiments to uncover patterns and insights about brain function. They often use programming languages like Python or R, statistical analysis, and machine learning algorithms under the supervision of senior scientists or data analysts. This role is ideal for early-career individuals with a background in neuroscience, data science, or a related field.
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Junior Data Science Neuroscience jobs near you
Senior Data Scientist (only USC and GC on W2)

Senior Data Scientist (only USC and GC on W2)

Ampstek

Phoenix, AZ • On-site

Contractor

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

Job description

Job Title: Senior Data Scientist

Location: Phoenix, Arizona - Onsite

Employment Type: Contract

Position Overview

• We are seeking a highly experienced Senior Data Scientist to support and enhance our AIOps (Artificial Intelligence for IT Operations) solution. This position plays a critical role in advancing our anomaly detection, root cause analysis, and intelligent automation capabilities across enterprise systems.

• The ideal candidate will bring deep expertise in machine learning, statistical modeling, and large-scale data analysis, with strong hands-on proficiency in Python and SQL. This individual will drive innovation in operational intelligence by leveraging anomaly detection, causal reasoning, time series modeling, and emerging GenAI techniques.

Key Responsibilities

• Design and implement scalable machine learning models for AIOps use cases including anomaly detection and root cause analysis.

• Develop and optimize advanced anomaly detection algorithms for infrastructure, application, and operational telemetry data.

• Apply causal reasoning frameworks to identify drivers of incidents and operational disruptions.

• Build and deploy time series forecasting and modeling solutions to predict performance degradation and system failures.

• Develop robust data pipelines and analytical workflows using Python and SQL.

• Integrate Generative AI (GenAI) techniques for intelligent summarization, incident triage, knowledge extraction, and automation.

• Collaborate with engineering, DevOps, and platform teams to operationalize ML models in production environments.

• Drive continuous improvement of model performance, scalability, and reliability.

• Mentor junior data scientists and contribute to best practices in MLOps and model governance.

Required Qualifications

• 6+ years of experience in data science or applied machine learning roles.

• Strong communication and stakeholder management skills.

• Strong proficiency in Python (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow or similar).

• Advanced SQL skills for data manipulation and analysis.

• Proven experience in anomaly detection techniques (statistical, ML-based, deep learning-based).

• Strong understanding and practical application of causal inference and causal reasoning methodologies.

• Hands-on experience with large-scale structured and time series datasets.

• Solid knowledge of time series modeling (ARIMA, Prophet, LSTM, state-space models, etc.).

• Experience deploying models into production environments.

• Strong analytical thinking and problem-solving capabilities.

Preferred Qualifications

• Experience in AIOps, IT Operations analytics, or observability platforms.

• Exposure to GenAI / LLM-based solutions for operational intelligence.

Email: preeti.verma@ampstek.com

Apply