THE ROLE
As a Developer / Data Scientist in our Data Analytics team, you will play a pivotal role in building out our analytics capabilities. You will be working alongside our Statistician and Lead Data Scientist to identify opportunities to develop and leverage new applications. You will get the opportunity to put your expertise to the test rapidly on use cases such as:
Supervised and unsupervised forecasting models and algorithms
Master and reference data/entity mapping
LLM fine-tuning and entity-recognition + data extraction
Data visualization/reporting
We are looking for your expertise in building and deploying models and end-to-end pipelines that significantly impact our client products, solutions, and engagements. You must have experience with machine learning and AI, but you will have access to our existing colleagues’ vast knowledge in that space.
Ideally, you are conversant on data modeling and can act as a partner to our architecture team to accelerate the delivery of our solutions to our AWS cloud-based environment.
Success in this role means delivering production-ready models that are actively used in client-facing tools, building stable and scalable data pipelines with clear documentation, and enabling faster team iteration through reusable components and streamlined data flows. A successful experience at the intersection of machine learning and organizational psychology or social sciences is a plus.
LOCATION AND TEAM STRUCTUREJoining the Amsterdam office.
Collaborating very closely with our Lead Data Scientist.
Providing technical expertise and ‘coding’ mentorship to data analysts.
Collaborating closely with our architecture team.
Interacting routinely with the broader Data Analytics and client teams (Head Data Analytics, Practice Leaders, Innovation team…).
Collaborate with the data analytics team and other stakeholders to identify and prioritize opportunities for innovative D&A applications.
Develop, test, and deploy machine learning models, entity mapping models, and reporting solutions (including NLP and AI technologies).
Design and implement data pipelines and APIs that facilitate seamless data circulation across teams and systems.
Stay abreast of industry trends and advancements in data science, ensuring our approaches and technologies remain at the cutting edge.
Advanced degree in Computer Science or Data Science.
Demonstrated ability to take ownership of data science projects from ideation to deployment with an emphasis on machine learning, NLP, and AI technologies (along with a strong understanding of their applications and limitations).
Strong programming skills in Python and strong familiarity with ML frameworks (e.g., TensorFlow, PyTorch). Bayesian modelling experience is very valuable.
Although not required immediately, some background and/or keen interest in developing a skillset in data visualization for reporting is considered very valuable (JS libraries such as Chart Js, C3/D3.js, Plotly or similar).
Excellent analytical and problem-solving abilities, with a keen eye for detail and accuracy.
Strong communication and interpersonal skills, with the ability to convey complex concepts to non-technical stakeholders.
Self-motivated with the ability to work independently and as part of a team in a fast-paced environment.
Prior experience in consulting or working closely with business stakeholders.
Direct experience developing and deploying models in NLP and LLM applications, particularly those that enhance client-facing tools or internal knowledge workflows.
3 to 5 years of experience in a similar role, with a heavy development/coding component.
Other requirements of interest:
Be familiar with architectures such as data lakes, lake houses, and data warehousing.
Experience with processes for data pipeline execution and managing their changes. Ability to maintain metadata specifications.
Experience understanding/specifying data models at conceptual and schema levels.
Experience with development tools such as VS Code, Jupyter notebooks, Jira, and Confluence.
Core Language: Expert proficiency in Python 3.x, deep knowledge of the standard library, best practices, and writing “Pythonic” code.
Data Ecosystem: Strong experience with Python data stack libraries (Pandas, PySpark) for data manipulation and Jupyter notebooks.
Database and Querying: Ability to write complex, optimized queries and understand data performance.
Data Visualization for Reporting: Familiarity with JavaScript libraries such as Chart.js, D3.js, Plotly, or similar is a plus.
Knowledge of the AWS Data tooling eco-system.
Understanding of AWS Glue, Athena, Redshift, RDS, and S3.
Motivated by working in a team and collaborating on ideas and daily tasks.
Excellent skills in documenting ideas via diagrams and narratives.
Ability to discuss concepts with technical and business audiences.
Top Skills
What We Do
At Spencer Stuart, we know how much leadership matters. We are trusted by organizations around the world to help them make the senior-level leadership decisions that have a lasting impact on their enterprises. Through our executive search, board and leadership advisory services, we help build and enhance high-performing teams for select clients ranging from major multinationals to emerging companies to nonprofit institutions.
Privately held since 1956, we focus on delivering knowledge, insight and results through the collaborative efforts of a team of experts — now spanning more than 70 offices, over 30 countries and more than 50 practice specialties. Boards and leaders consistently turn to Spencer Stuart to help address their evolving leadership needs in areas such as senior-level executive search, board recruitment, board effectiveness, succession planning, in-depth senior management assessment, employee engagement and many other facets of culture and organizational effectiveness.
