76 to 100 of 246 Permanent scikit-learn Jobs

Engineering, Mathematics, or related field with relevant coursework in machine learning/statistics, software engineering principles, and database systems Core Skills: Python, ML frameworks (TensorFlow/PyTorch/scikit-learn), SQL, distributed computing, version control Experience: 1+ years in ML engineering or data engineering Mindset: Self-motivated with a growth mindset, adaptable to fast-paced startup environment, comfortable More ❯

Engineering, Mathematics, or related field with relevant coursework in machine learning/statistics, software engineering principles, and database systems Core Skills: Python, ML frameworks (TensorFlow/PyTorch/scikit-learn), SQL, distributed computing, version control Experience: 1+ years in ML engineering or data engineering Mindset: Self-motivated with a growth mindset, adaptable to fast-paced startup environment, comfortable More ❯

focus on AI and machine learning Solid understanding of machine learning algorithms, data structures, and statistical modelling Experience with AI frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn Strong programming skills in languages such as Python, Java, or Scala Strong experience with cloud-based AI services and platforms (e.g., AWS, Azure, GCP, ServiceNow, SalesForce) Proven experience More ❯

data pipeline orchestration and a strong grasp of DevSecOps best practices in cloud-native environments • Hands-on experience with key tools and frameworks, including: o Python, NumPy, Pandas, scikit-learn o TensorFlow or PyTorch o Elasticsearch, Logstash, Kibana • Preferred Experience in GDS (Government Digital Services) or USDS (U.S. Digital Services) Education Requirement • Shall have at a minimum, a More ❯

What you'll bring: Experience in Data Science, or a related field Solid skills in Python and SQL for data manipulation and modelling Familiarity with ML libraries like Scikit-learn, PyTorch or TensorFlow Awareness of cloud platforms (Azure, AWS, or GCP) and data governance practices A strong analytical mindset, team spirit, and eagerness to learn from senior More ❯

Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps. Solid understanding of machine learning concepts, familiarity with frameworks such as scikit-learn, TensorFlow, or PyTorch. Collaborative and humble team player capable of working with cross-functional teams, including technical and non-technical stakeholders. Passion for learning new skills and staying More ❯

in statistics, probability, and machine learning fundamentals either through a STEM degree, formal training, or self-study. Fluency in Python and SQL, including experience with libraries like Pandas, Scikit-learn, or equivalent. Demonstrated ability to solve real-world problems pragmatically using data. Clear, structured communication especially the ability to explain complex topics simply. A growth mindset: curious, driven More ❯

DevOps, or Data Engineering with exposure to ML lifecycle. Hands-on experience building or maintaining ML workflows or pipelines. Strong Python skills and experience with tools like MLflow, Scikit-learn, or PyTorch. Familiarity with cloud platforms (especially Azure , AWS desirable). Good understanding of containerisation (Docker) and orchestration (e.g. Kubernetes). Exposure to CI/CD tools (GitHub More ❯

PhD with 4 years Deep expertise in big data platforms (e.g., Hadoop, Spark, Kafka) and multi-cloud environments (AWS, Azure, GCP) Experience with machine learning frameworks (e.g., TensorFlow, Scikit-learn, PyTorch) Strong programming skills in Python, Java, or Scala Familiarity with data pipeline development and real-time data processing Proven ability to design and implement data-intensive solutions More ❯

years of experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and More ❯

years of experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and More ❯

senior data science or quantitative academic position Strong Python programming skills, with the ability to write production-grade code Proficiency in core data science libraries (e.g. NumPy, Pandas, Scikit-learn) and familiarity with at least one deep learning framework (e.g. TensorFlow, PyTorch) A solid understanding of the full range of data science techniques, including supervised and unsupervised learning More ❯

background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

publications and preprints. Strong breadth and expertise in Statistical analysis, machine learning, data visualization, programming (Python, R, etc.), data cleaning and data manipulation. Tools: Python, R, SQL, TensorFlow, Scikit-learn, Tableau, Power BI. Ability to generate high quality ideas and be self-driven to explore. Strong experience in programming and comfortable modifying existing code-base. Experience with Python More ❯

data warehouse concepts and experience with data modeling, ETL/ELT pipelines, and performance tuning. Solid programming skills in Python for data transformation and machine learning (e.g., pandas, scikit-learn). Experience with BI tools such as Power BI and Tableau. Strong problem-solving and communication skills, with the ability to work across regions. 5+ years of experience More ❯

a related technical field. 3+ years of experience developing and deploying machine learning models. Deep proficiency in Python and major AI/ML libraries (e.g., PyTorch, HuggingFace Transformers, scikit-learn). Strong experience with end-to-end MLOps and model deployment in containerized environments. Familiarity with security-first software development practices (e.g., static code analysis, SBOMs, STIGs, zero More ❯

Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control More ❯

Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control More ❯

Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control More ❯

Tech Stack You'll Work With BI Tools : Power BI, Tableau, Looker, Google Data Studio Data Warehousing : Snowflake, BigQuery, Redshift, SQL Server Languages : SQL, DAX, Python (Pandas, NumPy, Scikit-learn - desirable) CRM Systems : Salesforce, HubSpot, Dynamics 365, Zoho ETL Tools : dbt, Fivetran, Talend, Alteryx AI/ML Frameworks (Desirable): Azure ML, AWS Sagemaker, HuggingFace, OpenAI APIs Version Control More ❯

What we're looking for 6+ years of experience in software engineering with strong focus on machine learning systems Deep proficiency in Python and ML ecosystem (e.g. PyTorch, scikit-learn, MLFlow) Solid understanding of data and model lifecycle management, versioning, and deployment Experience building ML infrastructure and model-serving pipelines in production environments Familiarity with cloud-based architecture More ❯

5+ years of experience in machine learning engineering, preferably in Ad Tech, Mar Tech, or related high-scale environments. Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Deep understanding of supervised, unsupervised, and reinforcement learning methods. Experience with GCP services such as Vertex AI, BigQuery ML, Dataflow, AI Platform Pipelines, and Dataproc. Solid knowledge More ❯

5+ years of experience in machine learning engineering, preferably in Ad Tech, Mar Tech, or related high-scale environments. Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Deep understanding of supervised, unsupervised, and reinforcement learning methods. Experience with GCP services such as Vertex AI, BigQuery ML, Dataflow, AI Platform Pipelines, and Dataproc. Solid knowledge More ❯

5+ years of experience in machine learning engineering, preferably in Ad Tech, Mar Tech, or related high-scale environments. Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Deep understanding of supervised, unsupervised, and reinforcement learning methods. Experience with GCP services such as Vertex AI, BigQuery ML, Dataflow, AI Platform Pipelines, and Dataproc. Solid knowledge More ❯

of key machine learning models, including Gradient Boosting Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and services including Sagemaker. Deep knowledge of Microsoft Excel in a commercial setting. You enjoy being Agile - you should More ❯