Position
Data Scientist
Company
Praxair India Private Limited (Linde)
Location
Bangalore, Karnataka, India
Job type
Regular / Permanent / Unlimited / Full-Time
Job mode
On-Site
Job requisition id
req33180
Years of experience
0 - 3 Years (Fresher / Entry Level)
Company description
Linde plc represents a premier global entity in the industrial gases and specialized engineering sector, establishing an authoritative operational presence across more than one hundred countries worldwide.
The organization maintains a steadfast mission dedicated to making the world significantly more productive on a daily basis through the continuous creation and implementation of superior technological solutions, products, and operational services.
Through cutting-edge process design, industrial automation, and technological innovation, the enterprise enhances customer operational success while simultaneously prioritizing environmental preservation and planetary sustainability.
Praxair India Private Limited operates as an essential operational arm of the broader organizational framework, bringing decades of deep market expertise and industrial gas distribution infrastructure to the regional ecosystem.
On April 1st, 2020, a major strategic consolidation occurred as Linde India Limited and Praxair India Private Limited successfully initiated and formed a joint venture entity known as LSAS Services Private Limited.
This joint venture was explicitly structured to deliver end-to-end Operations and Management (O&M) services to both founding organizations, allowing them to optimize field operations while continuing their respective commercial activities independently.
LSAS Services Private Limited carries forward a profound corporate mandate centered around sustainable growth, ecological stewardship, and continuous technological enhancement championed by both legacy operational entities.
The organization takes immense pride in maintaining a long-standing heritage of pioneering fundamental process engineering achievements that have repeatedly transformed standard practices across the industrial gases sector.
The company provides essential industrial gas applications, advanced gas production technologies, and comprehensive engineering services to an expansive list of crucial global end markets.
Primary industries served include heavy chemical processing, oil refining, food processing and cryogenic preservation, beverage carbonation, advanced electronics manufacturing, healthcare and medical oxygen production, primary metals processing, and specialized manufacturing.
Within the internal working environment, the enterprise fosters a culture where every single day represents a genuine opportunity for continuous learning, technical skill elevation, collective success sharing, and meaningful industrial contribution.
Employees are actively encouraged to step forward, embrace technical responsibility, and propel their professional careers inside one of the world's most respected industrial technology organizations.
Total employee compensation and perks packages are meticulously crafted to build a highly supportive, comfortable, engaging, and satisfying work environment for all team members.
Corporate benefit programs incorporate meaningful loyalty awards and structured recognition incentives aimed at rewarding long-term dedication and sustained high-level performance.
Generous annual leave allocations and structured time-off schemes ensure that staff members maintain an effective work-life balance while managing complex technical workloads.
The modern Bangalore operational site features fully equipped on-site eateries and dedicated dining facilities that promote healthy dining and social interaction during workday breaks.
Active Employee Resource Groups (ERGs) operate across the enterprise to provide robust peer support networks, nurture a deep sense of belonging, and facilitate cross-functional networking across various career stages.
Specialized internal community teams consistently organize collaborative events, sports activities, and professional development workshops that reinforce organizational cohesion.
Diversity and inclusive collaboration represent foundational operational pillars at Linde, underpinning every aspect of human capital management and talent acquisition.
The organization firmly recognizes that long-term commercial prosperity and innovative strength stem directly from embracing varied perspectives across internal teams, client bases, and global marketplaces.
As a global employer of choice, the business actively invests in comprehensive individual growth pipelines, welcoming disruptive ideas and upholding deep mutual respect for individual differences.
The corporate commitment to equality ensures that all recruitment, hiring, training, and promotional decisions are made strictly without regard to demographic background, gender, race, or belief system.
The leadership team views environmental, social, and corporate governance (ESG) standards not merely as external compliance checkboxes, but as central guiding principles driving strategic investments.
The organization actively develops technological solutions that directly reduce carbon intensity, lower industrial emissions, and assist global clients in achieving ambitious decarbonization targets.
By combining local operational strength with global expertise, Praxair India Private Limited continues setting benchmark performance levels in safety, reliability, and technological integration.
The organization continually invests in modernizing its digital infrastructure, creating state-of-the-art computational hubs and analytical centers to drive future industrial performance.
Employees benefit from extensive access to internal training portals, global technical communities, leadership mentorship programs, and ongoing educational support.
The corporate mantra "Be Linde. Be Limitless." reflects a belief that professional careers within the company should extend beyond rigid job descriptions to uplift surrounding communities and society at large.
The organizational leadership consistently encourages open dialogue, flat hierarchy communication, and cross-disciplinary solution building to solve the world's most demanding gas processing challenges.
Working with the company offers professionals an opportunity to participate directly in large-scale industrial projects that impact millions of lives daily across healthcare, energy, and tech supply chains.
Profile overview
The Data Scientist - AI Hub position represents a high-impact, entry-level engineering role dedicated to driving digital transformation across global enterprise operations through advanced artificial intelligence.
As an integral member of the centralized AI Hub based in Bangalore, the selected professional will directly contribute to expanding existing digital solutions and building novel AI software products.
The primary focus involves constructing intelligent algorithmic products designed to solve multifaceted operational, logistics, and engineering challenges across the entire corporate value chain.
The practitioner will interact with vast, highly heterogeneous datasets originating from continuous industrial plant sensors, supply chain systems, financial transaction databases, and operational logs.
Work involves handling structured, semi-structured, and unstructured data formats, transforming raw industrial telemetries into clean, standard formats suitable for high-precision predictive modeling.
The core daily responsibilities encompass designing, customizing, prototyping, and governing complete artificial intelligence applications built upon robust Machine Learning and Deep Learning frameworks.
The candidate will take full technical ownership of training algorithms, fine-tuning model hyper-parameters, evaluating mathematical error metrics, and validating statistical stability.
A critical aspect of the role involves providing extensive support for the replication and scaling of established AI products and data pipelines to other global regional nodes and legacy enterprise systems.
The team member will work closely with distributed international teams to ensure that algorithmic solutions developed in one market can be seamlessly containerized, deployed, and adapted globally.
The engineer will participate actively in defining system architectural designs, selecting optimal computational backends, and establishing precise data requirements for upcoming digital products.
The candidate will serve as a vital technical liaison, regularly communicating with non-technical business stakeholders, plant managers, and operational leads to identify core business pain points.
The role requires translating complex, unstructured business problems into rigorous, quantifiable machine learning formulations that deliver measurable financial and operational value.
The practitioner will oversee the complete lifecycle of data science initiatives, guiding ideas from conceptualization through hypothesis testing, rapid experimentation, prototype building, and final deployment.
The position demands a rigorous focus on deploying statistical models into live production environments, ensuring continuous inferencing stability, low latency, and high system reliability.
The engineer will implement continuous monitoring mechanisms to track model drift, concept drift, data corruption, and inferencing performance over time in production settings.
The job requires crafting clear, concise technical documentation detailing pipeline architectures, statistical assumptions, API contracts, model performance benchmarks, and code bases.
The role offers direct exposure to cutting-edge cloud infrastructure, automated machine learning pipelines, modern MLOps principles, and high-performance computing clusters.
The data scientist will work with advanced multivariate statistical techniques to uncover hidden patterns, root causes of operational anomalies, and equipment failure predictors.
The professional will collaborate with data engineers to establish efficient ETL/ELT data pipelines, ensuring reliable stream and batch data ingestion for machine learning backends.
The role involves conducting regular peer code reviews, adhering to best practices in software engineering, version control, automated testing, and modular software design.
The practitioner will explore, benchmark, and integrate emerging open-source machine learning libraries, deep learning architectures, and modern generative or predictive frameworks.
The engineer will participate in agile development sprints, daily standup meetings, product backlog grooming, and sprint retrospectives to ensure predictable and timely project delivery.
The position provides a unique learning environment where theoretical data science concepts are directly applied to physical, real-world industrial infrastructure and chemical process flows.
The team member will help create executive dashboards and interactive visual interfaces to communicate algorithm outputs, predictions, and recommendations to senior operational leaders.
The role emphasizes building ethical, explainable, and accountable AI solutions that adhere to corporate governance guidelines and global data protection regulations.
The data scientist will contribute to building centralized feature stores and reusable code libraries to streamline feature engineering across multiple enterprise data science projects.
The practitioner will actively assist in establishing operational key performance indicators (KPIs) to measure the actual ROI and business impact generated by deployed AI tools.
The position requires continuous adaptability to learn new operational domains quickly, ranging from cryogenic gas separation physics to dynamic fleet logistics routing.
The team member will participate in technical knowledge-sharing sessions, internal AI workshops, and technology hackathons to foster innovation within the global AI Hub community.
The role offers an exceptional launchpad for freshers and early-career professionals to build world-class expertise in applied enterprise AI, data engineering, and industrial digitalization.
Qualifications
Candidates must possess a Bachelor's Degree or Master's Degree in Data Science, Computational Statistics, Applied Mathematics, Computer Science, or an equivalent quantitative discipline.
Strong foundational understanding of and proven theoretical knowledge in Multivariate Statistics, Linear Algebra, Multivariable Calculus, and Probability Theory is strictly required.
Demonstrable practical experience in applying Machine Learning algorithms, including supervised, unsupervised, and reinforcement learning paradigms, to real-world datasets is essential.
Proven competence in Deep Learning concepts, neural network architectures, optimization techniques, loss function selection, and backpropagation mechanics is highly valued.
The candidate must display a proven ability to articulate complex business problems, structure logical analytical frameworks, and apply quantitative methodologies to derive actionable solutions.
Hands-on technical experience in comprehensive data preprocessing, data cleaning, missing value imputation, outlier handling, and normalization on large-scale noisy datasets is required.
Demonstrated mastery of feature engineering, automated feature selection, dimensionality reduction techniques (e.g., PCA, t-SNE), and exploratory data analysis (EDA).
Preferred background or prior exposure in an engineering, physical science, industrial technology, or technical operational environment is considered a distinct advantage.
High proficiency in Python programming language, including mastery over fundamental numerical and data manipulation libraries such as NumPy, Pandas, and SciPy.
Comprehensive knowledge of machine learning frameworks and modeling libraries in Python, such as Scikit-Learn, XGBoost, LightGBM, Statsmodels, PyTorch, or TensorFlow.
Strong practical capabilities in writing efficient, complex SQL queries for extracting, filtering, aggregating, and joining massive datasets across relational and non-relational database management systems.
Robust understanding of modern data architectural concepts, data warehousing, data lake structures, distributed storage systems, and schema design principles.
Practical experience in building interactive data visualizations and executive dashboards using modern business intelligence platforms such as Tableau, Power BI, or Matplotlib/Seaborn/Plotly.
Excellent result-driven, problem-solving mindset with the demonstrated ability to systematically guide a project from raw idea to rapid experimentation, prototype, and final implementation.
Outstanding verbal and written English communication skills, with high social competence, empathy, and the ability to convey complex technical concepts to non-technical stakeholders.
Experience with modern software engineering practices, including version control systems (Git, GitHub, GitLab), modular coding standards, object-oriented programming, and code documentation.
Preferred hands-on exposure to cloud computing environments, specifically Microsoft Azure cloud services, infrastructure, and native resource management tools.
Advantageous experience working with specialized cloud machine learning platforms, specifically Azure Machine Learning (Azure ML) for model training, registry, and deployment.
Desirable familiarity with workflow orchestration engines and data pipeline management tools such as Apache Airflow or Azure Data Factory.
Practical knowledge of open-source MLOps toolkits, particularly MLflow, for experiment tracking, model artifact logging, metric visualization, and model registry management.
Familiarity with containerization technologies such as Docker and container orchestration platforms like Kubernetes is highly beneficial for deployment tasks.
Understanding of software development lifecycle (SDLC) methodologies, including Agile, Scrum, and Kanban frameworks, ensuring efficient team collaboration.
Demonstrated capability to work effectively both as an independent individual contributor and as a collaborative team player within cross-functional, multi-cultural teams.
Strong analytical curiosity and an intrinsic drive to keep pace with rapid developments in artificial intelligence, foundation models, and modern data stack technologies.
Excellent time management and organizational skills, with a proven ability to prioritize concurrent technical tasks and meet project deadlines reliably.
Sound understanding of statistical hypothesis testing, A/B testing methodologies, confidence intervals, p-values, and experimental design.
Ability to analyze high-dimensional time-series data from industrial sensors, applying signal processing, rolling aggregations, and temporal feature extraction methods.
Knowledge of optimization algorithms, linear programming, mixed-integer programming, or evolutionary computation techniques applied to industrial operations is a plus.
High ethical standards regarding data privacy, intellectual property protection, data security protocols, and responsible AI governance.
Proven academic project portfolio, GitHub repositories, or Kaggle performance demonstrating practical applications of data science techniques to concrete datasets.
Additional info
The job requisition reference code for this position is officially designated as req33180, which must be referenced during all formal application queries and tracking.
The primary physical working location for this position is located at the modern corporate technology facility in Bangalore, Karnataka, India.
The designated working scheme for this role is strictly On-Site, requiring the employee to work directly from the Bangalore office location.
The employment contract type offered is Regular / Permanent / Unlimited / Full-Time Employee (FTE) status, providing strong long-term career stability and comprehensive benefits.
Interested and qualified candidates are encouraged to submit their complete application package, including a cover/motivation letter, detailed CV/resume, and academic transcripts/certificates via the official online job portal.
The job position was formally posted on September 15, 2026, and will remain open for active candidate applications until the official closing date of November 30, 2026.
Applicants are strongly advised to complete their online application submission early prior to the closing deadline to guarantee timely evaluation by the talent acquisition team.
All qualified job applicants will receive full and equal consideration for employment strictly without regard to race, skin color, religious belief, gender, national origin, or age.
The company maintains a strict non-discrimination policy protecting individuals regardless of physical or mental disability status, protected veteran status, pregnancy, sexual orientation, or gender identity/expression.
Praxair India Private Limited and Linde adhere strictly to all local, national, and international labor regulations prohibiting discrimination across all phases of recruitment.
Any job titles, designations, and gendered terminology used in the job description apply equally to individuals of all gender identities and expressions.
The linguistic structures and forms of speech used within job postings are selected solely for simplicity, clarity, and readability across global candidate pools.
Praxair India Private Limited maintains a deep commitment to acting responsibly towards its shareholders, commercial business partners, full-time employees, society, and the physical environment.
Corporate operational policies in every business area, geographical region, and facility location prioritize long-term ecological sustainability and ethical business governance.
The enterprise is dedicated to developing, manufacturing, and deploying cutting-edge industrial technologies that unite customer economic growth with environmental conservation goals.
Successful candidates will undergo a structured, merit-based candidate evaluation process comprising technical resume screening, coding assessments, technical interviews, and behavioral rounds.
The talent acquisition process evaluates candidates based on a balanced assessment of technical competence, domain aptitude, analytical thinking, and cultural alignment.
New hires will join a structured onboarding framework designed to accelerate domain learning, introduce corporate systems, and integrate freshers seamlessly into ongoing engineering projects.
Continuous mentorship will be provided by senior data scientists, enterprise architects, and engineering managers to foster rapid technical and professional growth.
Employees are provided with state-of-the-art computational hardware, cloud access keys, developer tools, and high-performance workstation setups required for advanced ML workloads.
The physical office campus in Bangalore features modern ergonomic workspaces, quiet focus areas, collaborative brainstorm hubs, high-speed networking, and fully equipped meeting rooms.
Regular internal performance reviews, goal-setting frameworks, and transparent merit-based appraisal systems ensure clear career advancement pathways within the global group.
The company offers ongoing professional development funding, allowing team members to acquire industry certifications, attend technical conferences, and complete specialized coursework.
Cross-functional mobility programs allow high-performing team members to explore diverse technical roles, business divisions, or international project assignments over time.
The global nature of the AI Hub ensures daily collaboration with international colleagues across Europe, the Americas, and the Asia-Pacific region, providing genuine global exposure.
Comprehensive employee health, medical, life, and accident insurance schemes are provided to safeguard employees and their families against unexpected health events.
Flexible leave policies, including personal leave, sickness leave, parental leave, and public holiday schedules, support healthy employee well-being and personal life commitments.
The organization actively encourages participation in sustainability drives, community outreach initiatives, STEM educational volunteering, and corporate social responsibility (CSR) programs.
Candidates who require specific interview accommodations or workplace adjustments due to disabilities are encouraged to notify the talent acquisition team during the application process.
To apply for this high-impact entry-level data science opportunity, candidates should access the TakeOff Talent job search portal or the official Linde online career center using reference code req33180.
Please click here to apply.
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