(Mji-201) - Lead Data Scientist

Dynatrace; Tarragona; Presencial; EUR 70.000 - 100.000; Jornada completa

Descripción de la vacante

A leading technology company in Spain is seeking a Senior Data Scientist to lead machine learning model development and data analysis. You will work on causal analysis and collaborate closely with stakeholders. A degree in a quantitative field and 10+ years of experience are required. This role offers the opportunity to mentor junior members and contribute to impactful product improvements.

Formación

• 10+ years of experience in data science, with 3+ years in a lead role.
• Expertise in causal analysis methods like A/B testing.
• Ability to articulate technical concepts to non-technical stakeholders.

Responsabilidades

• Explore and analyze large datasets for insights.
• Develop and deploy machine learning models.
• Collaborate with stakeholders to improve products.
• Mentor junior data scientists.
• Continuously monitor and enhance models.

Conocimientos

Causal analysis methods

Python (Pandas, NumPy, Scikit-Learn)

SQL

Communication skills

Big data technologies (Spark, Snowpark)

AWS services (S3, Lambda, EC2)

Data visualization (Plotly, Seaborn)

Data pipeline orchestration (Airflow, Luigi)

Educación

Degree in Engineering, Computer Science, Mathematics, or another quantitative field

Herramientas

Snowflake

Descripción del empleo

• Explore and analyse millions of rows of tabular data to uncover meaningful insights and build advanced machine-learning models.
• Design and implement causal analysis models to assess the impact of system performance on user experience, providing clear, actionable insights into customer behaviour.
• Develop and deploy machine learning models and workflows, transforming terabytes of traffic data into actionable insights that drive key business decisions.
• Lead the development and deployment of models, ensuring robustness, scalability, and reliability in production environments.
• Build automated solutions for business needs,

such as bot detection using advanced machine learning and statistical methods.

• Collaborate closely with product owners, engineers, and other stakeholders to translate analytical findings into impactful features and product improvements.
• Take ownership of technical direction, contribute to architectural decisions, identify technical debt, and advocate for opportunities for improvement.
• Mentor and support junior data scientists, enhancing team productivity, improving code quality, and fostering a culture of collaboration and learning.
• Continuously monitor and enhance model performance in partnership with the engineering team, improving model impact on user experience and system effectiveness.
• Qualifications
• A degree in Engineering, Computer Science, Mathematics, or another quantitative field.
• 10+ years of demonstrable / tenured experience in data / data science, including at least 3 years in a lead or senior IC role.
• Expertise in causal analysis methods (e.g., propensity score matching, A / B testing, uplift modeling)

with a demonstrated ability to analyse tabular data.

• Strong experience in Python (including Pandas, NumPy, and Scikit-Learn) for data processing and machine learning model construction.
• Proficiency in SQL, with the ability to write complex queries and optimise data retrieval from relational databases.
• Strong communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
• Familiarity with big data technologies such as Spark or Snowpark for processing and analysing large datasets efficiently.
• Hands-on experience working with Snowflake, particularly using Snowpark for scalable data engineering and machine learning workflows.
• Experience with AWS services (e.g., S3, Lambda, EC2) for managing machine learning infrastructure and deploying models in a cloud-native environment.
• Hands-on experience with data visualisation tools like Plotly, Seaborn, or other Python-based libraries to convey data insights effectively.
• Familiarity with data pipeline orchestration tools (e.g., Airflow, Luigi) to manage ETL / ELT workflows.
• Ability to operate in a fast-paced, dynamic environment, effectively prioritising multiple projects with competing deadlines.
• Additional Information
• All Insights team members are expected to travel at least 1 to 2 times per year for annual team meetings & events.

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