Position Details: Data Analyst

Description:

Data Analyst

• Role Overview
• We are looking for experienced Data Analysts (MLE Bench) to contribute to
benchmark-driven evaluation projects focused on real-world machine learning
systems.

This role involves hands-on analytical work with production-like
datasets, metrics, and ML outputs to help evaluate, diagnose, and improve
the performance of advanced AI systems.

The ideal candidate is comfortable working at the intersection of data
analysis and machine learning, with strong analytical rigor and the ability
to work with real datasets and ML evaluation workflows.

• What does day-to-day life look like?

• · *Analyze structured and unstructured datasets generated from ML
training, inference, and evaluation pipelines.

• · *Define, compute, and validate metrics used to evaluate model
performance and behavior.

• · *Investigate data distributions, model outputs, failure modes,
and edge cases relevant to benchmark tasks.

• · *Write and run Python and SQL code to analyze data, create
reports, and support evaluation workflows.

• · *Validate data quality, consistency, and correctness across
datasets and experiments.

• · *Create clear, well-documented analytical artifacts and
reproducible analysis workflows.

• · *Collaborate with ML engineers and researchers to design
challenging, real-world evaluation scenarios for MLE Bench.

• *Requirements
• · *Minimum 3+ years of experience as a Data Analyst or
Analytics-focused Engineer.

• · *Strong proficiency in Python for data analysis.

• · *Solid experience with SQL and relational datasets.

• · *Experience analyzing ML outputs and evaluation metrics.

• · *Strong understanding of statistics and analytical reasoning.

• · *Ability to work with large, complex datasets and draw reliable
insights.

• · *Experience writing clean, readable, and well-documented
analytical code.

• · *Excellent spoken and written English communication skills.

• Req #2 ML Engineer
• Role Overview
• We are looking for experienced Machine Learning Engineers (MLE Bench) to
contribute to benchmark-driven evaluation projects focused on real-world
machine learning systems.

This role involves hands-on work with
production-grade ML codebases, model training and evaluation pipelines, and
deployment-oriented workflows to help assess and improve the capabilities
of advanced AI systems.

The ideal candidate is comfortable bridging research and engineering,
working deeply with models, data, and infrastructure in realistic ML
environments.

• What does day-to-day life look like?

• · *Work with real-world ML codebases to support MLE Bench–style
evaluation tasks.

• · *Build, run, and modify model training, evaluation, and inference
pipelines.

• · *Prepare datasets, features, and metrics for ML benchmarking and
validation.

• · *Debug, refactor, and improve production-like ML systems for
correctness and performance.

• · *Evaluate model behavior, failure modes, and edge cases relevant
to benchmark tasks.

• · *Write clean, reproducible, and well-documented Python code for
ML workflows.

• · *Participate in code reviews to ensure high standards of
engineering quality.

• · *Collaborate with researchers and engineers to design
challenging, real-world ML engineering tasks for AI system evaluation.

• *Requirements
• · *Minimum 3+ years of overall experience as a Machine Learning
Engineer or Software Engineer (ML-focused).

• · *Strong proficiency in Python for machine learning and data
workflows.

• · *Hands-on experience with model training, evaluation, and
inference pipelines.

• · *Solid understanding of machine learning fundamentals
(supervised/unsupervised learning, evaluation metrics, optimization).

• · *Experience working with ML frameworks (e.g., PyTorch,
TensorFlow, JAX, or similar).

• · *Ability to understand, navigate, and modify complex, real-world
ML codebases.

• · *Experience writing readable, reusable, and maintainable
production-quality code.

• · *Strong problem-solving and debugging skills.

• · *Excellent spoken and written English communication skills.

• Req #3

Python Developer

• Role Overview
• We are seeking a Python Developer with strong expertise in FastAPI to join
an exciting Reinforcement Learning (RL) Gym project.

You will design,
build, and optimize scalable APIs, collaborate with researchers and
engineers, and deliver high-quality backend services to support
reinforcement learning experiments and simulations.

Prior RL Gym experience
is not mandatory but would be a plus.

• What does day-to-day life look like?

• · *Design, build, and maintain FastAPI-based services for
experimentation workflows and simulation environments.

• · *Collaborate with ML engineers to expose APIs for training,
evaluation, and benchmarking.

• · *Write efficient, production-grade Python code with a strong
emphasis on scalability and maintainability.

• · *Troubleshoot performance issues, optimize pipelines, and ensure
smooth deployment of applications.

• *Requirements
• · *4+ years of professional Python development experience including
3+ years of strong experience in FastAPI

• · *Experience with REST APIs, async programming, and API lifecycle
management.

• · *Solid understanding of software engineering best practices
(testing, CI/CD, version control, design patterns).

• · *Familiarity with NumPy, Pandas, and PyTorch/TensorFlow is a
plus.

• · *Good to have: Exposure to Reinforcement Learning environments
(OpenAI Gym, Gymnasium, Stable Baselines, or custom environments) & SQL
experience

• · *Bachelor’s or Master’s degree in Computer Science, Engineering,
or related field.

• Req #4
• Role Overview
• We are looking for a Technical Content Writer who can deliver clear,
technically accurate content and support data-driven work with hands-on
experience using JSON and public datasets.

You’ll analyze datasets to
extract business insights and present reasoning through well-structured
documentation, notebooks, or clearly explained technical artifacts.

You will collaborate with researchers and stakeholders, translating complex
findings into concise narratives and actionable recommendations.

Strong
communication, output quality, and attention to detail are essential.

• What does day-to-day life look like?

• · Produce clear, well-structured technical documentation and
written deliverables.

· Analyze public datasets to derive business insights and respond
to key analytical questions.

· Clearly explain reasoning and logic in notebooks or other
suitable formats.

· Work with JSON-based data and ensure outputs are accurate and
well-organized.

· Use Python scripting (as needed) to support data exploration,
validation, and reproducible analysis.

· Ensure comprehensive documentation and traceability of methods,
assumptions, and findings.

· Collaborate and communicate with researchers and stakeholders to
refine insights and deliverables.

• Requirements
• · Minimum 3+ years of relevant experience as a technical content
writer, analyst, or software developer.

· Strong technical writing skills with experience producing clear,
accurate, and structured content.

· Comfort working with data formats like JSON and interpreting
datasets.

· Working knowledge of Python for data exploration/validation (not
a core engineering role).

· Familiarity with notebooks and/or scripting workflows to support
analysis and documentation.

· Good understanding of code quality, formatting, and documentation
best practices.

· Strong analytical abilities and business sense to draw
appropriate conclusions and communicate them clearly.

· Excellent spoken and written English communication skills.

Hi,

Please find the Active Requirement.

Location: Remote

Shift Time: 2pm to 11pm

Req #1

Data Analyst

Role Overview

We are looking for experienced Data Analysts (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems.

This role involves hands-on analytical work with production-like datasets, metrics, and ML outputs to help evaluate, diagnose, and improve the performance of advanced AI systems.

The ideal candidate is comfortable working at the intersection of data analysis and machine learning, with strong analytical rigor and the ability to work with real datasets and ML evaluation workflows.

What does day-to-day life look like?

·          Analyze structured and unstructured datasets generated from ML training, inference, and evaluation pipelines.

·          Define, compute, and validate metrics used to evaluate model performance and behavior.

·          Investigate data distributions, model outputs, failure modes, and edge cases relevant to benchmark tasks.

·          Write and run Python and SQL code to analyze data, create reports, and support evaluation workflows.

·          Validate data quality, consistency, and correctness across datasets and experiments.

·          Create clear, well-documented analytical artifacts and reproducible analysis workflows.

·          Collaborate with ML engineers and researchers to design challenging, real-world evaluation scenarios for MLE Bench.

Requirements

·          Minimum 3+ years of experience as a Data Analyst or Analytics-focused Engineer.

·          Strong proficiency in Python for data analysis.

·          Solid experience with SQL and relational datasets.

·          Experience analyzing ML outputs and evaluation metrics.

·          Strong understanding of statistics and analytical reasoning.

·          Ability to work with large, complex datasets and draw reliable insights.

·          Experience writing clean, readable, and well-documented analytical code.

·          Excellent spoken and written English communication skills.

Req #2 ML Engineer

Role Overview

We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems.

This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems.

The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.

What does day-to-day life look like?

·          Work with real-world ML codebases to support MLE Bench–style evaluation tasks.

·          Build, run, and modify model training, evaluation, and inference pipelines.

·          Prepare datasets, features, and metrics for ML benchmarking and validation.

·          Debug, refactor, and improve production-like ML systems for correctness and performance.

·          Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks.

·          Write clean, reproducible, and well-documented Python code for ML workflows.

·          Participate in code reviews to ensure high standards of engineering quality.

·          Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.

Requirements

·          Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused).

·          Strong proficiency in Python for machine learning and data workflows.

·          Hands-on experience with model training, evaluation, and inference pipelines.

·          Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization).

·          Experience working with ML frameworks (e.g., PyTorch, TensorFlow, JAX, or similar).

·          Ability to understand, navigate, and modify complex, real-world ML codebases.

·          Experience writing readable, reusable, and maintainable production-quality code.

·          Strong problem-solving and debugging skills.

·          Excellent spoken and written English communication skills.

Req #3

Python Developer

Role Overview

We are seeking a Python Developer with strong expertise in FastAPI to join an exciting Reinforcement Learning (RL) Gym project.

You will design, build, and optimize scalable APIs, collaborate with researchers and engineers, and deliver high-quality backend services to support reinforcement learning experiments and simulations.

Prior RL Gym experience is not mandatory but would be a plus.

What does day-to-day life look like?

·          Design, build, and maintain FastAPI-based services for experimentation workflows and simulation environments.

·          Collaborate with ML engineers to expose APIs for training, evaluation, and benchmarking.

·          Write efficient, production-grade Python code with a strong emphasis on scalability and maintainability.

·          Troubleshoot performance issues, optimize pipelines, and ensure smooth deployment of applications.

Requirements

·          4+ years of professional Python development experience including 3+ years of strong experience in FastAPI

·          Experience with REST APIs, async programming, and API lifecycle management.

·          Solid understanding of software engineering best practices (testing, CI/CD, version control, design patterns).

·          Familiarity with NumPy, Pandas, and PyTorch/TensorFlow is a plus.

·          Good to have: Exposure to Reinforcement Learning environments (OpenAI Gym, Gymnasium, Stable Baselines, or custom environments) & SQL experience

·          Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Req #4

Role Overview

We are looking for a Technical Content Writer who can deliver clear, technically accurate content and support data-driven work with hands-on experience using JSON and public datasets.

You’ll analyze datasets to extract business insights and present reasoning through well-structured documentation, notebooks, or clearly explained technical artifacts.

You will collaborate with researchers and stakeholders, translating complex findings into concise narratives and actionable recommendations.

Strong communication, output quality, and attention to detail are essential.

What does day-to-day life look like?

·          Produce clear, well-structured technical documentation and written deliverables.

·          Analyze public datasets to derive business insights and respond to key analytical questions.

·          Clearly explain reasoning and logic in notebooks or other suitable formats.

·          Work with JSON-based data and ensure outputs are accurate and well-organized.

·          Use Python scripting (as needed) to support data exploration, validation, and reproducible analysis.

·          Ensure comprehensive documentation and traceability of methods, assumptions, and findings.

·          Collaborate and communicate with researchers and stakeholders to refine insights and deliverables.

Requirements

·          Minimum 3+ years of relevant experience as a technical content writer, analyst, or software developer.

·          Strong technical writing skills with experience producing clear, accurate, and structured content.

·          Comfort working with data formats like JSON and interpreting datasets.

·          Working knowledge of Python for data exploration/validation (not a core engineering role).

·          Familiarity with notebooks and/or scripting workflows to support analysis and documentation.

·          Good understanding of code quality, formatting, and documentation best practices.

·          Strong analytical abilities and business sense to draw appropriate conclusions and communicate them clearly.

·          Excellent spoken and written English communication skills.Hi,

Please find the Active Requirement.

Location: Remote

Shift Time: 2pm to 11pm

Req #1

Data Analyst

• Role Overview
• We are looking for experienced Data Analysts (MLE Bench) to contribute to
benchmark-driven evaluation projects focused on real-world machine learning
systems.

This role involves hands-on analytical work with production-like
datasets, metrics, and ML outputs to help evaluate, diagnose, and improve
the performance of advanced AI systems.

The ideal candidate is comfortable working at the intersection of data
analysis and machine learning, with strong analytical rigor and the ability
to work with real datasets and ML evaluation workflows.

• What does day-to-day life look like?

• · *Analyze structured and unstructured datasets generated from ML
training, inference, and evaluation pipelines.

• · *Define, compute, and validate metrics used to evaluate model
performance and behavior.

• · *Investigate data distributions, model outputs, failure modes,
and edge cases relevant to benchmark tasks.

• · *Write and run Python and SQL code to analyze data, create
reports, and support evaluation workflows.

• · *Validate data quality, consistency, and correctness across
datasets and experiments.

• · *Create clear, well-documented analytical artifacts and
reproducible analysis workflows.

• · *Collaborate with ML engineers and researchers to design
challenging, real-world evaluation scenarios for MLE Bench.

• *Requirements
• · *Minimum 3+ years of experience as a Data Analyst or
Analytics-focused Engineer.

• · *Strong proficiency in Python for data analysis.

• · *Solid experience with SQL and relational datasets.

• · *Experience analyzing ML outputs and evaluation metrics.

• · *Strong understanding of statistics and analytical reasoning.

• · *Ability to work with large, complex datasets and draw reliable
insights.

• · *Experience writing clean, readable, and well-documented
analytical code.

• · *Excellent spoken and written English communication skills.

• Req #2 ML Engineer
• Role Overview
• We are looking for experienced Machine Learning Engineers (MLE Bench) to
contribute to benchmark-driven evaluation projects focused on real-world
machine learning systems.

This role involves hands-on work with
production-grade ML codebases, model training and evaluation pipelines, and
deployment-oriented workflows to help assess and improve the capabilities
of advanced AI systems.

The ideal candidate is comfortable bridging research and engineering,
working deeply with models, data, and infrastructure in realistic ML
environments.

• What does day-to-day life look like?

• · *Work with real-world ML codebases to support MLE Bench–style
evaluation tasks.

• · *Build, run, and modify model training, evaluation, and inference
pipelines.

• · *Prepare datasets, features, and metrics for ML benchmarking and
validation.

• · *Debug, refactor, and improve production-like ML systems for
correctness and performance.

• · *Evaluate model behavior, failure modes, and edge cases relevant
to benchmark tasks.

• · *Write clean, reproducible, and well-documented Python code for
ML workflows.

• · *Participate in code reviews to ensure high standards of
engineering quality.

• · *Collaborate with researchers and engineers to design
challenging, real-world ML engineering tasks for AI system evaluation.

• *Requirements
• · *Minimum 3+ years of overall experience as a Machine Learning
Engineer or Software Engineer (ML-focused).

• · *Strong proficiency in Python for machine learning and data
workflows.

• · *Hands-on experience with model training, evaluation, and
inference pipelines.

• · *Solid understanding of machine learning fundamentals
(supervised/unsupervised learning, evaluation metrics, optimization).

• · *Experience working with ML frameworks (e.g., PyTorch,
TensorFlow, JAX, or similar).

• · *Ability to understand, navigate, and modify complex, real-world
ML codebases.

• · *Experience writing readable, reusable, and maintainable
production-quality code.

• · *Strong problem-solving and debugging skills.

• · *Excellent spoken and written English communication skills.

• Req #3

Python Developer

• Role Overview
• We are seeking a Python Developer with strong expertise in FastAPI to join
an exciting Reinforcement Learning (RL) Gym project.

You will design,
build, and optimize scalable APIs, collaborate with researchers and
engineers, and deliver high-quality backend services to support
reinforcement learning experiments and simulations.

Prior RL Gym experience
is not mandatory but would be a plus.

• What does day-to-day life look like?

• · *Design, build, and maintain FastAPI-based services for
experimentation workflows and simulation environments.

• · *Collaborate with ML engineers to expose APIs for training,
evaluation, and benchmarking.

• · *Write efficient, production-grade Python code with a strong
emphasis on scalability and maintainability.

• · *Troubleshoot performance issues, optimize pipelines, and ensure
smooth deployment of applications.

• *Requirements
• · *4+ years of professional Python development experience including
3+ years of strong experience in FastAPI

• · *Experience with REST APIs, async programming, and API lifecycle
management.

• · *Solid understanding of software engineering best practices
(testing, CI/CD, version control, design patterns).

• · *Familiarity with NumPy, Pandas, and PyTorch/TensorFlow is a
plus.

• · *Good to have: Exposure to Reinforcement Learning environments
(OpenAI Gym, Gymnasium, Stable Baselines, or custom environments) & SQL
experience

• · *Bachelor’s or Master’s degree in Computer Science, Engineering,
or related field.

• Req #4
• Role Overview
• We are looking for a Technical Content Writer who can deliver clear,
technically accurate content and support data-driven work with hands-on
experience using JSON and public datasets.

You’ll analyze datasets to
extract business insights and present reasoning through well-structured
documentation, notebooks, or clearly explained technical artifacts.

You will collaborate with researchers and stakeholders, translating complex
findings into concise narratives and actionable recommendations.

Strong
communication, output quality, and attention to detail are essential.

• What does day-to-day life look like?

• · Produce clear, well-structured technical documentation and
written deliverables.

· Analyze public datasets to derive business insights and respond
to key analytical questions.

· Clearly explain reasoning and logic in notebooks or other
suitable formats.

· Work with JSON-based data and ensure outputs are accurate and
well-organized.

· Use Python scripting (as needed) to support data exploration,
validation, and reproducible analysis.

· Ensure comprehensive documentation and traceability of methods,
assumptions, and findings.

· Collaborate and communicate with researchers and stakeholders to
refine insights and deliverables.

• Requirements
• · Minimum 3+ years of relevant experience as a technical content
writer, analyst, or software developer.

· Strong technical writing skills with experience producing clear,
accurate, and structured content.

· Comfort working with data formats like JSON and interpreting
datasets.

· Working knowledge of Python for data exploration/validation (not
a core engineering role).

· Familiarity with notebooks and/or scripting workflows to support
analysis and documentation.

· Good understanding of code quality, formatting, and documentation
best practices.

· Strong analytical abilities and business sense to draw
appropriate conclusions and communicate them clearly.

· Excellent spoken and written English communication skills.

Hi,

Please find the Active Requirement.

Location: Remote

Shift Time: 2pm to 11pm

Req #1

Data Analyst

Role Overview

We are looking for experienced Data Analysts (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems.

This role involves hands-on analytical work with production-like datasets, metrics, and ML outputs to help evaluate, diagnose, and improve the performance of advanced AI systems.

The ideal candidate is comfortable working at the intersection of data analysis and machine learning, with strong analytical rigor and the ability to work with real datasets and ML evaluation workflows.

What does day-to-day life look like?

·          Analyze structured and unstructured datasets generated from ML training, inference, and evaluation pipelines.

·          Define, compute, and validate metrics used to evaluate model performance and behavior.

·          Investigate data distributions, model outputs, failure modes, and edge cases relevant to benchmark tasks.

·          Write and run Python and SQL code to analyze data, create reports, and support evaluation workflows.

·          Validate data quality, consistency, and correctness across datasets and experiments.

·          Create clear, well-documented analytical artifacts and reproducible analysis workflows.

·          Collaborate with ML engineers and researchers to design challenging, real-world evaluation scenarios for MLE Bench.

Requirements

·          Minimum 3+ years of experience as a Data Analyst or Analytics-focused Engineer.

·          Strong proficiency in Python for data analysis.

·          Solid experience with SQL and relational datasets.

·          Experience analyzing ML outputs and evaluation metrics.

·          Strong understanding of statistics and analytical reasoning.

·          Ability to work with large, complex datasets and draw reliable insights.

·          Experience writing clean, readable, and well-documented analytical code.

·          Excellent spoken and written English communication skills.

Req #2 ML Engineer

Role Overview

We are looking for experienced Machine Learning Engineers (MLE Bench) to contribute to benchmark-driven evaluation projects focused on real-world machine learning systems.

This role involves hands-on work with production-grade ML codebases, model training and evaluation pipelines, and deployment-oriented workflows to help assess and improve the capabilities of advanced AI systems.

The ideal candidate is comfortable bridging research and engineering, working deeply with models, data, and infrastructure in realistic ML environments.

What does day-to-day life look like?

·          Work with real-world ML codebases to support MLE Bench–style evaluation tasks.

·          Build, run, and modify model training, evaluation, and inference pipelines.

·          Prepare datasets, features, and metrics for ML benchmarking and validation.

·          Debug, refactor, and improve production-like ML systems for correctness and performance.

·          Evaluate model behavior, failure modes, and edge cases relevant to benchmark tasks.

·          Write clean, reproducible, and well-documented Python code for ML workflows.

·          Participate in code reviews to ensure high standards of engineering quality.

·          Collaborate with researchers and engineers to design challenging, real-world ML engineering tasks for AI system evaluation.

Requirements

·          Minimum 3+ years of overall experience as a Machine Learning Engineer or Software Engineer (ML-focused).

·          Strong proficiency in Python for machine learning and data workflows.

·          Hands-on experience with model training, evaluation, and inference pipelines.

·          Solid understanding of machine learning fundamentals (supervised/unsupervised learning, evaluation metrics, optimization).

·          Experience working with ML frameworks (e.g., PyTorch, TensorFlow, JAX, or similar).

·          Ability to understand, navigate, and modify complex, real-world ML codebases.

·          Experience writing readable, reusable, and maintainable production-quality code.

·          Strong problem-solving and debugging skills.

·          Excellent spoken and written English communication skills.

Req #3

Python Developer

Role Overview

We are seeking a Python Developer with strong expertise in FastAPI to join an exciting Reinforcement Learning (RL) Gym project.

You will design, build, and optimize scalable APIs, collaborate with researchers and engineers, and deliver high-quality backend services to support reinforcement learning experiments and simulations.

Prior RL Gym experience is not mandatory but would be a plus.

What does day-to-day life look like?

·          Design, build, and maintain FastAPI-based services for experimentation workflows and simulation environments.

·          Collaborate with ML engineers to expose APIs for training, evaluation, and benchmarking.

·          Write efficient, production-grade Python code with a strong emphasis on scalability and maintainability.

·          Troubleshoot performance issues, optimize pipelines, and ensure smooth deployment of applications.

Requirements

·          4+ years of professional Python development experience including 3+ years of strong experience in FastAPI

·          Experience with REST APIs, async programming, and API lifecycle management.

·          Solid understanding of software engineering best practices (testing, CI/CD, version control, design patterns).

·          Familiarity with NumPy, Pandas, and PyTorch/TensorFlow is a plus.

·          Good to have: Exposure to Reinforcement Learning environments (OpenAI Gym, Gymnasium, Stable Baselines, or custom environments) & SQL experience

·          Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

Req #4

Role Overview

We are looking for a Technical Content Writer who can deliver clear, technically accurate content and support data-driven work with hands-on experience using JSON and public datasets.

You’ll analyze datasets to extract business insights and present reasoning through well-structured documentation, notebooks, or clearly explained technical artifacts.

You will collaborate with researchers and stakeholders, translating complex findings into concise narratives and actionable recommendations.

Strong communication, output quality, and attention to detail are essential.

What does day-to-day life look like?

·          Produce clear, well-structured technical documentation and written deliverables.

·          Analyze public datasets to derive business insights and respond to key analytical questions.

·          Clearly explain reasoning and logic in notebooks or other suitable formats.

·          Work with JSON-based data and ensure outputs are accurate and well-organized.

·          Use Python scripting (as needed) to support data exploration, validation, and reproducible analysis.

·          Ensure comprehensive documentation and traceability of methods, assumptions, and findings.

·          Collaborate and communicate with researchers and stakeholders to refine insights and deliverables.

Requirements

·          Minimum 3+ years of relevant experience as a technical content writer, analyst, or software developer.

·          Strong technical writing skills with experience producing clear, accurate, and structured content.

·          Comfort working with data formats like JSON and interpreting datasets.

·          Working knowledge of Python for data exploration/validation (not a core engineering role).

·          Familiarity with notebooks and/or scripting workflows to support analysis and documentation.

·          Good understanding of code quality, formatting, and documentation best practices.

·          Strong analytical abilities and business sense to draw appropriate conclusions and communicate them clearly.

·          Excellent spoken and written English communication skills.

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