13 of 13 Statsmodels Jobs in London

non-technical stakeholders through effective data visualisation and building of reporting frameworks Comfortable with Python data science libraries such as pandas, scikit-learn, numpy, statsmodels Strong SQL experience including analytic functions, performance tuning, data wrangling Ability to work collaboratively and proactively in a fast-paced environment alongside scientists, engineers and More ❯

experimental design Experience with marketing mix modeling, incrementality testing, or causal inference Proficiency in Python for data analysis and statistical modeling (pandas, numpy, scipy, statsmodels) Familiarity with machine learning libraries such as scikit-learn Experience with SQL for data extraction and manipulation Demonstrated ability to translate analytical findings into business More ❯

product-focused roles. Deep understanding of LTV modeling, forecasting, and experimental design. Proficiency in Python for data analysis and modeling (e.g., pandas, scikit-learn, statsmodels). Advanced SQL skills and experience working with large datasets in modern data environments. Experience working with cross-functional growth or marketing teams. Competent user More ❯

skills, business acumen, and the ability to translate complex models into actionable insights for non-technical stakeholders. Tools/Frameworks : Scikit-learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy More ❯

skills, business acumen, and the ability to translate complex models into actionable insights for non-technical stakeholders. Tools/Frameworks : Scikit-learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy More ❯

modeling, forecasting, and experimental design. Comprehension of A/B testing methodologies Proficiency in Python for data analysis and modeling (e.g., pandas, scikit-learn, statsmodels). Strong SQL skills and experience working with large datasets in modern data environments. Experience working with cross-functional growth or marketing teams. Competent user More ❯

of machine learning techniques specific to time series analysis Technical Proficiency:Expertise in Python and SQL, with significant experience using time series libraries (e.g., Statsmodels, Facebook Prophet, TensorFlow Time Series) and cloud technologies (e.g., AWS S3/EC2) alongside CI/CD tools (GitHub Actions, Jenkins, AWS CodePipeline) Preferred Qualifications More ❯

pricing Digital media or entertainment Expertise in Python and SQL, with a strong grounding in statistical and machine learning techniques (e.g. scikit-learn, XGBoost, statsmodels). Experience working with modern cloud data stacks (e.g. Snowflake, BigQuery, Redshift) and transformation tools like dbt. Familiarity with A/B testing, causal inference More ❯

pricing Digital media or entertainment Expertise in Python and SQL, with a strong grounding in statistical and machine learning techniques (e.g. scikit-learn, XGBoost, statsmodels). Experience working with modern cloud data stacks (e.g. Snowflake, BigQuery, Redshift) and transformation tools like dbt. Familiarity with A/B testing, causal inference More ❯

insights. Capability to manage projects end-to-end and produce good outcomes without much supervision. Proficiency with data manipulation and modelling tools - e.g., pandas, statsmodels, R. Experience with scientific computing and tooling - e.g., NumPy, SciPy, R, Matlab, Mathematica, BLAS. Degree in Statistics, Mathematics, Physics or equivalent. Bonus: Experience implementing solutions More ❯

in probability and statistics. Experience developing code collaboratively and implementing solutions in a production environment. Proficiency with data manipulation and modelling tools - e.g., pandas, statsmodels, R. Experience with scientific computing and tooling - e.g., NumPy, SciPy, Matlab, etc. Self-driven with the capability to efficiently manage projects end-to-end. Experience More ❯

have 1-2 years’ experience in data science. Coding experience (e.g. Python, SQL). Knowledge and understanding of a data science library (e.g. SKLearn, Statsmodels, Scipy). Desirable Further development experience (e.g. R, C++). Knowledge of Git and GitHub. Previous experience in a trading environment. Experience with a data More ❯

Job Description We are seeking a seasoned data scientist to join our global, growing data science team. This role involves working across multiple markets, with a focus on Europe, including recent expansion into France and potential future moves into Germany. More ❯