Senior Data Scientist IRC292482

Description

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Requirements

We’re looking for a teammate with:
The ideal candidate will have hands-on experience building and shipping production ML
systems, with deep proficiency in Python and the modern AWS ML stack:
• Python Expertise: Python is your primary language. You write clean, well-structured
code and are comfortable owning end-to-end ML workflows — from data ingestion and
EDA through model training, validation, and deployment.
• AWS SageMaker: Practical, hands-on experience with SageMaker as your primary ML
platform — including SageMaker Studio, Training Jobs, Pipelines, Model Registry, and
real-time or batch Inference Endpoints.
• Machine Learning Fundamentals: Strong grounding in supervised and unsupervised
ML methods — gradient boosting, neural networks, dimensionality reduction, clustering,
and survival/time-to-event models. Experience with frameworks such as scikit-learn,
XGBoost, LightGBM, and PyTorch or TensorFlow.
• Feature Engineering and Data Wrangling: Demonstrated ability to extract, clean, and
engineer features from complex, multi-source datasets using Python (pandas, numpy,
PySpark) and SQL against platforms such as Snowflake or similar cloud data
warehouses.
• Model Evaluation and Experimentation: Rigorous approach to model evaluation —
cross-validation, holdout testing, calibration, and business-metric alignment. Experience
with experiment tracking tools such as MLflow or SageMaker Experiments.
• Cloud and Infrastructure Awareness: Solid AWS experience beyond SageMaker,
including S3, IAM, Lambda, and Step Functions. Familiarity with infrastructure-as-code
or CI/CD patterns for ML pipelines is a plus.
• Data Platform Integrations: Hands-on experience working with Snowflake, Apache
Iceberg, or similar modern data platforms as upstream data sources for ML pipelines.
Familiarity with Qlik Cloud Analytics or Qlik Talend Cloud is a strong plus.

Beyond technical skills, we’re looking for someone who brings:
• Bias for Impact: You care about whether your models actually change decisions — not
just whether they score well on a leaderboard.
• Strong Communication: Ability to explain model behavior, limitations, and business
implications to non-technical stakeholders clearly and without jargon.
• Security and Governance Mindset: Awareness of responsible AI practices, data
privacy considerations, model auditability, and the importance of reproducibility in
production ML systems.
• Collaborative Spirit: Comfortable working across functions and levels, from data
engineers and CSMs to the C-suite.

Job responsibilities

Here’s how you’ll be making an impact:
• Build and Deploy ML Models: Design, train, evaluate, and deploy supervised and
unsupervised machine learning models on AWS SageMaker — including classification,
regression, clustering, and anomaly detection use cases.
• Own the Feature Engineering Pipeline: Develop robust, reusable feature pipelines in
Python that transform raw data from Snowflake, our client Cloud Analytics, and other sources
into high-quality model inputs.
• Integrate with the Data Ecosystem: Connect model pipelines to our client Cloud Analytics,
our client Talend Cloud, Snowflake, and Apache Iceberg, ensuring data freshness, lineage,
and governance standards are met.
• Operationalize Models at Scale: Leverage SageMaker Pipelines, Model Registry, and
Endpoints to bring models into production reliably — with monitoring, drift detection, and
retraining workflows in place.
• Support LLM-Augmented Workflows: Collaborate with AI Systems Engineers to
integrate predictive model outputs as structured signals into agentic AI pipelines
deployed on AWS Bedrock.
• Translate Signals into Action: Partner with Customer Success, Sales, and Analytics
stakeholders to translate model outputs into actionable insights, dashboards, and
automated intervention triggers.
• Iterate and Instrument: Operate in a fast-moving incubator environment — prototype
quickly, measure model performance against business outcomes, and continuously
refine based on real usage signals.
• Document and Govern: Maintain clear model cards, experiment logs, and data lineage
documentation in support of our client’s AI governance framework and ISO 42001 compliance
posture.

What we offer

Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. 

Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands-on opportunities to grow personally and professionally.

Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem-solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting-edge and impactful solutions shaping the world today.

Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way!

High-trust organization. We are a high-trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do.

About GlobalLogic

GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.