Data Scientist Mid-Level

Why Valtech? We’retheexperience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience.

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.

We are proud of:

• The work we do and the innovation we drive

• Our values of share, care and dare

• A workplace culture that fosters creativity, diversity and autonomy

• Our borderless, global framework, which enables seamless collaboration

The role

As a Data Scientist, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 3+ YEARS of experience, a growth mindset and a drive to make a lasting impact.

You will thrive in this role if you are:

• A curious problem solver who challenges the status quo

• A collaborator who values teamwork and knowledge-sharing

• Excited by the intersection of technology, creativity and data

• Experienced in Agile methodologies and consulting (a plus)

Role responsibilities

• Lead the development of analytical, statistical, machine learning, and applied AI solutions for business and client use cases.

• Translate business questions into structured analytical approaches, modeling strategies, hypotheses, features, evaluation methods, and measurable outputs.

• Design and execute analyses and models across use cases such as segmentation, forecasting, propensity modeling, anomaly detection, experimentation analysis, recommendation-oriented analysis, and decision support.

• Work independently with structured, semi-structured, and selected unstructured datasets to derive insights and develop business-relevant solutions.

• Build, refine, and maintain notebook-based workflows and reproducible analytical assets in Databricks and other cloud-based environments.

• Apply machine learning and AI methods to support classification, scoring, summarization, pattern detection, feature generation, and business process improvement use cases.

• Support the evaluation and practical application of LLM-enabled or AI-assisted workflows where they strengthen business analysis, insight generation, or decision support.

• Participate in model training, tuning, validation, performance review, and comparative evaluation across different analytical and AI approaches.

• Document assumptions, methodology, feature logic, model decisions, evaluation criteria, limitations, and findings clearly and consistently.

• Partner with Data Analysts, AI Scientists, AI Engineers, Analytics Engineers, Data Engineers, and Architects to ensure solutions align with business needs, data realities, and technical constraints.

• Improve delivery quality by identifying opportunities for better reproducibility, stronger evaluation practices, clearer documentation, and more scalable analytical workflows.

• Follow established governance, privacy, and responsible data and AI use standards in day-to-day work.

Must have qualifications

To be considered for this role, you must meet the following essential qualifications:

• Strong working knowledge of statistics, probability, machine learning, and analytical problem solving.

• Ability to independently manage recurring data science workstreams and deliver reliable outputs with minimal oversight.

• Strong understanding of supervised and unsupervised learning approaches, feature engineering, model evaluation, error analysis, and analytical problem framing.

• Ability to work effectively with structured, semi-structured, and selected unstructured datasets.

• Working knowledge of experimentation design, model validation, and the interpretation of analytical and predictive outputs in business contexts.

• Growing familiarity with applied AI methods, including LLM-enabled workflows, text-oriented analysis, and AI-assisted feature extraction or classification.

• Strong familiarity with notebook-based development and collaborative data science workflows, including Databricks.

• Strong curiosity about patterns, behaviors, drivers, and how advanced analytical methods support decision-making and business value.

• Strong attention to detail and disciplined approach to validating data, logic, methodology, and outputs.

• Strong written and verbal communication skills in English, including the ability to explain analytical methods and findings clearly to non-technical stakeholders.

• Ability to balance technical rigor with practical business and delivery realities.

• Ability to collaborate effectively across distributed teams in the Americas and work across functions, time zones, and client contexts.

Tools / Platforms

Programming / Data Science

• Python

• Jupyter Notebooks

• Pandas

• NumPy

• scikit-learn

• SciPy

• Statsmodels

• XGBoost

• LightGBM

Data Science Workbench / Lakehouse Platforms

• Databricks

• Databricks notebooks

• Databricks Machine Learning

• Apache Spark

• PySpark

• MLflow

Data & Querying

• SQL

• BigQuery

• Snowflake

• Other cloud data platforms as needed

Cloud & AI Platforms

• Google Cloud Platform (GCP)

• Vertex AI

• Microsoft Azure

• Azure AI services

• Azure Machine Learning

• Other cloud-based machine learning and analytics platforms as needed

Applied AI / LLM Support

• OpenAI-compatible APIs or enterprise LLM platforms as relevant to the client environment

• Prompt evaluation and structured testing workflows

• Embedding, text analysis, and unstructured data processing patterns

• Model and workflow evaluation tooling as relevant to the client environment

Visualization / Analysis Support

• Matplotlib

• Seaborn

• Plotly

• Looker

• Power BI

• Tableau

Workflow / Collaboration / Versioning

• Git

• GitHub

• Azure DevOps

• Other collaboration and code management tools as relevant to the client environment

Certifications

Preferred, not required

• Databricks associate-level training or certification

• Google Cloud data, ML, or AI training

• Microsoft Azure data, ML, or AI training

• Python, machine learning, experimentation, or applied AI coursework

• Statistics, forecasting, or analytical modeling training

Collaboration / Stakeholder Expectations

• Serves as a dependable data science partner to internal teams and client stakeholders across modeling, analysis, and applied AI needs.

• Collaborates closely with Data Analysts to ensure analytical and predictive outputs connect clearly to reporting, decision-making, and business context.

• Works with AI Scientists and AI Engineers where use cases involve LLMs, unstructured data, agentic patterns, or more advanced AI solution design.

• Partners with Analytics Engineers, Data Engineers, and Architects to ensure workflows are supported by scalable data pipelines, governed structures, and reliable environments.

• Participates confidently in client-facing discussions by explaining methodology, model logic, findings, limitations, and practical implications in clear business language.

• Helps improve team consistency by strengthening notebooks, documentation, evaluation methods, and reusable analytical practices.

AI Fluency / AI-Assisted Data Science Expectations

Expected to be an active adopter of approved AI-enabled analytical, coding, experimentation, documentation, and productivity workflows that improve the quality and speed of data science work. Uses AI-assisted workflows to support exploratory analysis, feature thinking, code and notebook development, model documentation, experiment design, analytical summarization, and stakeholder communication while maintaining human accountability for method selection, statistical reasoning, validation, interpretation, and final recommendations.

Understands that AI-generated code, modeling suggestions, analytical summaries, or methodological recommendations must be reviewed against source data, assumptions, statistical rigor, business context, governance expectations, and reproducibility standards before use. Demonstrates curiosity and practical enthusiasm for applying AI to improve analytical leverage, decision support, and delivery quality without weakening scientific discipline or human judgment.

At this level, AI fluency means reliable use within workstreams. Expected to apply approved AI-assisted workflows to improve delivery quality, repeatability, documentation, and stakeholder communication, and to help junior practitioners understand where AI can and cannot be used responsibly.

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn.

Commitment to reaching all kinds of people

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all.

The benefits

Beyond a competitive compensation package, we offer:

• Flexibility, with remote and hybrid work options (country-dependent)

• Career advancement, with international mobility and professional development programs

• Learning and development, with access to cutting-edge tools, training and industry experts

• Medical, dental, and vision insurance for you and your family, plus employer contributions to Health Savings Accounts

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process.

Your application process

Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps.Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.

⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses.

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world.

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more.

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate.

Are you ready to create what’s next? Join us.

For applicants in California, please see Valtech's CPRA Privacy Notice here.

Originally posted on Himalayas