R&D Deployment Scientist Job at Randstad (Pomezia)

Field R&D Lead Data Scientist - Industrial Focus

Our global Field R&D team is a central part of the company strategy. The team fo...

Location

United States , Remote

Salary:

149665.00 - 269396.00 USD / Year

Cloud Software Group

Expiration Date

Until further notice

Requirements

5+ years of experience in advanced data analytics and delivery of demonstrations, projects, engagements or deployed software applications
5+ years of experience in applying analytics to industry verticals such as Energy, Manufacturing, or similar
Superior communication and storytelling skills with data
Capability to formulate a real-world problem into a mathematical equivalent, propose various solutions, compare and contrast them, deploy the solution, validate the results, and present the results to technical and non-technical stakeholders
5+ years of experience with Python or R and some knowledge of SQL
Excellent communication and collaboration skills, with the ability to work effectively in a team environment and communicate technical concepts to non-technical stakeholders
Strong problem-solving skills, with the ability to identify key areas for improvement and develop data-driven solutions to address them
A Master’s or higher degree in STEM (Computer Science, Statistics, Data Science, Engineering, Science, or related analytical field of study) with graduate classes in statistics and data mining

Job Responsibility

Delve deep into energy, manufacturing, or similar types of analytical and data science challenges
Engage with customers through presales support and post-sales success projects
Perform and guide R&D topics in the field of applied machine learning and AI
Create reusable data models, workflows and test suites in order to streamline project delivery
Provide input into product management and engineering for the product roadmap
Innovate in the areas of application and deployment of machine learning
Tool Kit Development: create demos and templates with data science libraries
Technical marketing: create white papers, blogs and content for the Spotfire user community
Represent the team as a speaker or instructor in industry events and external conferences
Participate in technical customer engagements through understanding Spotfire use cases, providing guidance, and building prototypes

What we offer

Healthcare
Life insurance
Disability benefits
401(k) plan and company match

Fulltime

Principal Engineer - Test

We are looking for detail-oriented and forward-thinking Test Engineer to ensure ...

Location

United Kingdom , Cambridge

Salary:

Not provided

Codvo AI

Expiration Date

Until further notice

Requirements

12+ years of experience in software testing, QA, or validation roles for cloud-native applications using Microsoft and .NET technologies
Proficient in designing automated testing frameworks
Hands-on experience with Azure DevOps, CI/CD pipelines, and containerized test environments
Strong understanding of API testing, performance profiling, and security testing (including OWASP top 10)
Excellent problem-solving skills, with the ability to analyse complex technical challenges and propose scalable solutions
Experience working in Agile teams and collaborating across global R&D locations
Demonstrated ability to mentor junior team members fostering a culture of continuous learning and innovation

Job Responsibility

Perform functional, performance, and security testing on cloud-native services deployed on Microsoft Azure
Design and implement automated test suites for APIs, service components, and AI pipelines
Automate the evaluation of AI system outputs to ensure accuracy, consistency, and safety of responses
Collaborate with developers and data scientists to establish service-level quality metrics and observability hooks
Validate services against AI regulatory frameworks and ensure traceability, fairness, and robustness in outcomes
Participate in threat modelling and security validation of exposed APIs and AI services
Provide feedback early in the lifecycle to reduce defects and improve design
Mentor junior testers, encourage continuous learning, and contribute to a culture of innovation

Fulltime

Principal Engineer - Test

We are looking for detail-oriented and forward-thinking Test Engineer to ensure ...

Location

India , Bengaluru

Salary:

Not provided

Codvo AI

Expiration Date

Until further notice

Requirements

12+ years of experience in software testing, QA, or validation roles for cloud-native applications using Microsoft and .NET technologies
Proficient in designing automated testing frameworks
Hands-on experience with Azure DevOps, CI/CD pipelines, and containerized test environments
Strong understanding of API testing, performance profiling, and security testing (including OWASP top 10)
Excellent problem-solving skills, with the ability to analyse complex technical challenges and propose scalable solutions
Experience working in Agile teams and collaborating across global R&D locations
Demonstrated ability to mentor junior team members fostering a culture of continuous learning and innovation

Job Responsibility

Perform functional, performance, and security testing on cloud-native services deployed on Microsoft Azure
Design and implement automated test suites for APIs, service components, and AI pipelines
Automate the evaluation of AI system outputs to ensure accuracy, consistency, and safety of responses
Collaborate with developers and data scientists to establish service-level quality metrics and observability hooks
Validate services against AI regulatory frameworks and ensure traceability, fairness, and robustness in outcomes
Participate in threat modelling and security validation of exposed APIs and AI services
Provide feedback early in the lifecycle to reduce defects and improve design
Mentor junior testers, encourage continuous learning, and contribute to a culture of innovation

Fulltime

Senior Project Manager

As a Senior Project Manager, you are passionate about experience innovation and ...

Location

India , Bengaluru

Salary:

Not provided

Valtech

Expiration Date

Until further notice

Requirements

Minimum 5 years of professional project management experience, with a demonstrable track record of delivering Data, Analytics, or AI/ML solutions end-to-end
Bachelor's degree in Computer Science, Engineering, Information Systems, Business, or a related discipline. Master's degree or MBA is a plus
Proven delivery experience across at least two of the following verticals: Automotive, Agriculture, Manufacturing (e.g., IoT/telematics, smart farming, Industry 4.0, MES integration, predictive maintenance, computer vision on the factory floor)
Strong working knowledge of modern data and AI technologies, including cloud data platforms (Azure, AWS, or GCP), data pipelines, MLOps, and at least foundational familiarity with generative AI and LLM-based solutions
Hands-on experience leading Agile (Scrum/Kanban) and hybrid delivery teams, including distributed and offshore squads
Excellent stakeholder management skills-comfortable engaging C-level sponsors, plant managers, R&D heads, and technical specialists with equal credibility
Strong commercial acumen: budget ownership, vendor management, SOW shaping, and change control
Demonstrated ability to navigate ambiguity, prioritize ruthlessly, and drive outcomes in environments where data maturity varies significantly
Excellent written and verbal communication skills, including the ability to translate technical concepts for non-technical audiences

Job Responsibility

Delivery leadership: Lead the full lifecycle of Data & AI projects-discovery, design, build, deployment, and adoption-across multiple concurrent engagements
Planning & execution: Develop and maintain detailed project plans, budgets, RAID logs, and resource forecasts
manage scope, timelines, and dependencies using Agile, Waterfall, or hybrid approaches as appropriate
Stakeholder management: Serve as the primary point of contact for client executives, product owners, and technical leads
clearly communicate progress, risks, trade-offs, and value realization
Cross-functional coordination: Orchestrate work across data engineers, data scientists, ML engineers, architects, business analysts, and domain SMEs to deliver integrated outcomes
Industry contextualization: Apply working knowledge of Automotive, Agriculture, and Manufacturing operations (e.g., connected vehicle data, precision agriculture, predictive maintenance, supply-chain analytics) to shape delivery and de-risk execution
Governance & quality: Enforce delivery standards, model governance, data quality, security, and responsible-AI practices in line with organizational and regulatory requirements
Commercial accountability: Track financials against forecast, manage change requests, identify upsell opportunities, and ensure margin and utilization targets are met
Continuous improvement: Run retrospectives, capture lessons learned, and contribute to internal delivery playbooks, estimation models, and capability uplift

What 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

Fulltime

Data Scientist Co-op

We are seeking a Data Science Intern to join our dynamic team at Ericsson. In th...

Location

Canada , Montreal

Salary:

Not provided

Ericsson

Expiration Date

Until further notice

Requirements

Currently enrolled in a Bachelor's, Master's, or PhD program in Data Analytics, Computer Science, Engineering, Business Analytics, or a related field (must maintain student status for the duration of the internship)
Academic or practical experience with SQL and relational databases
Academic or practical experience with Python scripting
Academic or practical experience with Power BI (or similar BI/visualization tools)
Foundational knowledge of AI/ML concepts, automation, or data-driven decision support (e.g., coursework, projects, or online certifications)
Familiarity or interest in learning AWS CLI or similar cloud CLIs
Familiarity or interest in learning APIs, automation frameworks, or AI-related tools
Strong analytical mindset, curiosity, and a demonstrated willingness to learn new tools and techniques
Good communication and teamwork skills, with the ability to collaborate in a multicultural, distributed team environment
Ability to work in a structured, process-oriented way, paying attention to detail and documentation

Job Responsibility

Support the design and development of operational dashboards for R&D stakeholders, under the guidance of senior team members
Assist in translating analytics strategy into solution designs and architecture guidelines, contributing to design discussions and documentation
Help create analytics solutions aligned with stakeholder needs by preparing datasets, building prototypes, and documenting approaches
Collaborate with other analytics and engineering teams to understand existing solutions and promote reuse of components and best practices
Learn to apply AI/ML concepts and automation to enhance analytics solutions, including model development, evaluation, and basic deployment steps
Assist in the development and documentation of dashboards, reports, databases, and interfaces using tools such as SQL, Python, and Power BI
Participate in unit testing, support acceptance testing, and help troubleshoot and resolve defects with support from mentors
Provide operational support such as data loading, job scheduling, monitoring, and basic troubleshooting of data pipelines and dashboards

Fulltime

Data Scientist

Location

Singapore , Singapore

Salary:

Not provided

Nicoll Curtin

Expiration Date

Until further notice

Requirements

Must be based in Singapore (remote-first team
flexible working environment).
Bachelor’s degree, Master or PhD in Data Science, Computer Science, Statistics, or related field.
6+ years of hands-on experience delivering data science projects from research to production, ideally in mission-critical domains.
Proven expertise with LLMs and modern NLP frameworks (LangChain, LlamaIndex, OpenAI APIs, HuggingFace, etc.).
Strong foundation in machine learning, graph analytics, anomaly detection, and unstructured data workflows.
Advanced proficiency in Python and SQL with a track record of writing clean, modular, testable, and production-ready code.
Experience with large-scale data platforms (e.g., PySpark, BigQuery) and scalable ML deployments.
Solid knowledge of MLOps and DataOps, including CI/CD, monitoring, retraining, and reproducibility.
Comfortable in Linux, Git, Docker, and modern collaboration workflows.

Job Responsibility

Lead complex R&D initiatives: drive research and innovation in LLMs, NLP, machine learning, and graph analytics, turning advanced techniques into production-grade solutions.
Own the full data science lifecycle: from discovery, framing, and exploration to deployment, customer delivery, and long-term monitoring.
Shape ambiguous challenges into well-defined problem statements and design practical, state-of-the-art solutions aligned with business and regulatory needs.
Engage directly with customers and stakeholders: collaborate to co-design use cases, set success metrics, and ensure solutions are adopted, measurable, and impactful.
Mentor and guide peers: elevate technical excellence, foster knowledge-sharing, and set best practices for experimentation, testing, and deployment.
Prototype rapidly: explore new ideas and validate hypotheses quickly, while balancing innovation with scalability and maintainability.
Ensure production success: design, implement, and optimize pipelines for data integration, validation, monitoring, and retraining to sustain long-term model performance.
Communicate effectively: distill technical complexity into compelling business insights, helping stakeholders make informed decisions.
Champion excellence in execution: enforce best practices in MLOps, DataOps, and software engineering to deliver reproducible, maintainable, and scalable solutions.
Continuously improve tooling and processes that accelerate delivery, experimentation, and collaboration across the data science function.

Fulltime

IT Project Manager - ELN Platforms (Electronic Lab Notebook) & Scientific Data Systems

The IT Project Manager – ELN, Scientific Data Platforms & Manufacturing Systems ...

Location

India , Hyderabad

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

10-15+ years in IT delivery with program-level ownership
8+ years delivering ELN or scientific data platforms in regulated environments
5+ years of MES implementation or integration experience (e.g., batch execution, eBR)
5-8 years of GxP validation (CSV/CSA) ownership across lab and/or manufacturing systems
5+ years driving adoption across scientific and/or manufacturing organizations
5+ years integrating ELN with LIMS/CDS/SDMS AND/OR MES with lab systems
Proven decision-making authority (not support roles)
Notice Period: 30 Days

Job Responsibility

Lead full lifecycle: strategy → design → configuration → integration → validation → deployment → adoption → optimization
Own delivery across lab systems and manufacturing platforms (MES)
Align scientific data strategy with manufacturing execution and batch data flows
Deliver against measurable outcomes: Adoption, Data quality, Compliance, Cycle time
Translate experimental workflows (R&D, QC) and manufacturing processes into structured digital systems
Standardize experiment design (ELN) and batch records & execution workflows (MES)
Ensure traceability from development → production
Own CSV/CSA validation strategy across ELN, MES, integrated lab/manufacturing systems
Ensure compliance with GxP, 21 CFR Part 11, ALCOA+ principles
Accountable for audit readiness and validation documentation completeness

Fulltime

Pharma Data Science Consultant

As a Pharma Data Science Consultant, you will contribute to high-impact projects...

Location

Japan , Tokyo

Salary:

Not provided

Amaris Consulting

Expiration Date

Until further notice

Requirements

Proven experience as a Data Scientist with strong hands-on expertise in modeling and feature engineering
Mandatory background in the pharmaceutical or life sciences industry (pharma, biotech, CRO, healthcare analytics)
Strong knowledge of pharmaceutical data types: Clinical trial data, R&D or biomarker data, Real-world evidence (RWE), Commercial / sales / market access data
Proficiency in Python and/or R, with common data science libraries (pandas, NumPy, scikit-learn, etc.)
Experience working with structured and semi-structured datasets
Ability to work autonomously and provide data-driven recommendations
Strong analytical mindset and ability to bridge technical and business perspectives

Job Responsibility

Lead end-to-end data science projects, from problem definition to model deployment and interpretation of results
Advise stakeholders on data selection and prioritization, leveraging strong pharmaceutical domain knowledge
Perform advanced feature engineering on complex healthcare and pharmaceutical datasets
Develop, validate, and optimize machine learning and statistical models for pharma use cases
Translate business and scientific questions into robust data-driven solutions
Collaborate with data engineers, product owners, and business teams to ensure data and model relevance
Communicate data assumptions, methodologies, and results clearly to non-technical stakeholders
Contribute to best practices in data science, including documentation and reproducibility

What we offer

A dynamic international environment with opportunities to work on diverse projects
Strong career development path with training and internal mobility opportunities
Access to a global community of experts and knowledge-sharing initiatives
Involvement in innovative and high-impact projects within the life sciences sector

Fulltime

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R&D Deployment Scientist

Job Description

Job Responsibility

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