Senior Data Scientist (m/f/d) - #2106371

Xempus


Date: vor 15 Stunden
Stadt: München
Vertragstyp: Ganztags
Arbeitsplan: Volle Tag
Xempus
Who We Are

We are Xempus, Germany´s leading independent Software-as-Service (SaaS) platform for the management and distribution of pension, life and health insurance. Our mission: making pension, life and health insurance digital and understandable, efficient and accessible for everyone. Since 2007, we have been constantly working to drive the digitalization of the insurance industry. Here at Xempus, we believe that together we can make a difference – no matter where we are! Whether from one of our offices or from home – join us and together we create a more secure future for everyone!

The role

We are seeking a talented and experienced Senior Data Scientist to join our dynamic team. In this role, you will lead the development of advanced machine learning models that drive personalized insurance product recommendations and optimize consultation processes for our agents as well as automate administrative processes related to user activity. You will work closely with data engineering, analytics, and product teams to ensure the creation of impactful solutions, collaborating on deployment and integration with a focus on model performance and continuous improvement.

Key Responsibilities

  • Design, develop, and refine sophisticated machine learning models and data models to address business challenges
  • Perform exploratory data analysis (EDA) and feature engineering to extract meaningful insights and improve model accuracy
  • Collaborate with data engineering and software engineering teams to ensure models are effectively deployed into production environments, providing guidance and support on integration and testing
  • Monitor model performance and data quality, analyzing feedback to identify opportunities for refinement and optimization
  • Communicate complex analysis and model results clearly to stakeholders, providing insights to support strategic decision-making
  • Contribute to the development of automated workflows for data preprocessing and model retraining, ensuring models stay relevant over time

What We Are Looking For

  • Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Statistics, or a related field.
  • 7+ years of experience in data science, analytics, or related roles, with a strong focus on model development
  • Proficiency in Python, with extensive experience in machine learning frameworks like Scikit-learn, TensorFlow, or PyTorch
  • Experience with version control systems, particularly git
  • Experience with data quality tools and testing frameworks (e.g., Great Expectations, pytest)
  • Strong SQL skills for querying and analyzing data from existing data warehouses
  • Experience in developing and implementing machine learning models for personalized recommendations and process optimization
  • Experience in setting up and managing machine learning pipelines
  • Proficiency in exploratory data analysis (EDA) and feature engineering
  • Experience with data visualization (e.g., Tableau)
  • Knowledge of natural language processing (NLP) techniques and libraries
  • Strong understanding of statistical analysis, machine learning algorithms, and data modeling techniques
  • Knowledge of best practices in model evaluation, validation, and performance monitoring
  • Strong analytical and problem-solving skills
  • Excellent communication skills, especially in explaining complex models and results to non-technical stakeholders

Optional Skills

  • Experience with big data tools like Apache Spark (PySpark)
  • Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and cloud-based data warehouses (e.g., Snowflake, Redshift)
  • Knowledge of MLOps practices and tools such as Docker, Kubernetes, and MLflow
  • Experience with automated workflow tools like Apache Airflow
  • Familiarity with advanced feature management tools
  • Advanced knowledge of database management and optimization
  • Familiarity with dbt for data transformation and analytics

Why Xempus

  • Join one of the leading insurtechs in Europe as it enters its next growth phase 
  • Find creative freedom and quick decision-making structures in a dynamic, innovative environment 
  • Opportunity to participate in one of the most generous employee stock option programs in the industry 
  • Very attractive contribution to the company pension scheme
  • Corporate health insurance (600€ reimbursement of various medical and pharmacy costs per year)
  • Work with a team of amazing colleagues with great team spirit (company parties, charity events e.g.) 
  • Have the option of hybrid working - for family friendliness and maximum flexibility in your everyday life. You can find out more here.
  • Broad range of personal & professional development opportunities: individual annual training budget, free courses, and a transparent career development model 
  • Various health offerings such as bike leasing and EGYM Wellpass
  • Modern offices in a central location, including free drinks & fruit 
  • We offer you an option for an unpaid extra holiday in addition to your 30-day holiday entitlement per year

Contact

Does that sound like your kind of job? Then apply now!

If you have any questions, difficulties uploading your data, or require any assistance with the recruitment process, Marta Von Deimling ([email protected]) is happy to help.

We’d love to hear from you!

About Us

At XEMPUS, +180 people work on a very special vision: We make the future plannable. We have been shaping the digital transformation in the insurance industry since 2007. We know what our successful future depends on: our team, the people behind the name XEMPUS.

We have ambitious goals. To achieve those goals, we need you!

We are an equal opportunity employer and ensure that no applicant is subject to less favourable treatment on the grounds of gender, gender identity, marital status, race, colour, nationality, ethnicity, age, sexual orientation, socio-economic, responsibilities for dependants, physical or mental disability. Any hiring decision are made on the basis of skills, qualifications and experiences.

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