76 to 100 of 261 scikit-learn Jobs

biggest names in private equity. Ideal Candidate Experience: 5+ years in data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience with More ❯

on experience in AI or ML in a professional environment (3-5 years preferred) • Strong knowledge of machine learning model development, deployment, and modern ML libraries (TensorFlow, PyTorch, scikit-learn, etc.) • Solid programming background with experience using statistical and signal analysis libraries • Experience with neural network architectures including deep learning models • Understanding of transformer architectures and attention mechanisms More ❯

to-text or customer feedback analysis Ability to contribute to client discussions, understand business needs, and translate them into ML solutions Familiarity with modern ML frameworks (e.g. HuggingFace, Scikit-learn, PyTorch) Comfortable working in a consultancy-style environment with multiple projects Nice to Have Experience with prompt engineering or fine-tuning LLMs Cloud platform experience (Azure, GCP preferred More ❯

Bring: 3+ years' experience building and deploying ML models, ideally in NLP or computer vision domains. Expert-level Python and SQL, with solid experience using libraries like Pandas, Scikit-Learn, TensorFlow, etc. Proven experience working with BigQuery and big data pipelines on GCP . Deep understanding of statistics, machine learning algorithms, and data modelling. Strong analytical mindset with More ❯

new. You should have: 2+ years of experience in machine learning or data science roles Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Solid understanding of machine learning algorithms and statistical methods Experience working with cloud platforms (AWS, GCP, or Azure) Familiarity with MLOps tools and practices is a plus A More ❯

experience with statistical modelling or machine learning techniques (regression analysis, clustering, classification, predictive modelling) through coursework, internships, or independent projects You are proficient in Python (especially pandas, numpy, scikit-learn, or similar libraries) and comfortable performing data analysis using Jupyter notebooks or similar tools You are comfortable writing clear, efficient SQL for extracting, cleaning, and preparing datasets, demonstrated More ❯

programming in Java/Python, including API integrations Knowledge of RESTful API development and integration Understanding of version control systems (e.g., Git) Specific tools include: Python Libraries like Scikit-learn or TensorFlow SQL and NoSQL databases Soft skills include: Self-starter Collaborative Fast-paced and adaptable to change Attention to detail Strong problem-solving skills Excellent communication skills 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 ❯

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 ❯

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 ❯

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 ❯

grow and shape the data science team and its role within the wider business. What We’re Looking For Strong technical foundation with proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and cloud platforms (GCP or AWS). Experience with modern data warehouses (BigQuery, Snowflake, Redshift). Proven experience in deploying machine learning models or optimisation algorithms into 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 ❯

DB experience * Proven experience in time series analysis and forecasting, preferably in a commercial or industrial setting. * Strong proficiency in Python, including libraries such as Pandas, NumPy, and scikit-learn for data manipulation and modelling. * Experience with machine learning algorithms. * Proficient in data visualization techniques to effectively communicate insights from time series data. * Strong problem-solving skills and 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 ❯