Luxoft – Data Scientist

Job Description:
Luxoft is hiring a Data Scientist to drive data intelligence and machine learning innovation for its Digital Oilfield (DOF) systems. This role is ideal for professionals who thrive at the crossroads of engineering, analytics, and applied AI. You will be responsible for transforming raw, noisy oilfield data into actionable insights that power predictive decision-making for global energy operations. The position calls for a mix of strong statistical expertise, hands-on Python programming skills, and the ability to apply data-driven solutions to real-world industrial challenges.

As part of a multidisciplinary team of engineers, developers, and data experts, you’ll design, validate, and operationalize models that predict field behavior, detect anomalies, and optimize production systems. You will work with complex time-series and sensor data, build ML algorithms for forecasting and classification, and deploy models that enhance the performance and reliability of oilfield operations. This role also involves collaborating with MLOps teams to bring models from prototype to production, ensuring scalability and robustness.

This position offers the chance to contribute to the next generation of digital transformation in the energy industry. You’ll engage directly with engineering teams across geographies, design domain-specific visualizations and dashboards, and translate analytical insights into measurable business outcomes. Occasional business travel to Kuwait may be required. Luxoft provides a stimulating environment where analytical minds can experiment with AI, NLP, and LLM-powered automation to revolutionize industrial operations.

Roles & Responsibilities:

• Analyze large-scale operational datasets (including time-series, tabular, and sensor logs) to uncover patterns, correlations, and opportunities for optimization.

• Design and train machine learning models for forecasting, anomaly detection, and predictive analytics tailored to oilfield operations.

• Collaborate with production engineers and domain specialists to define KPIs, convert business challenges into measurable data science tasks, and validate models against real-world results.

• Develop clear, insightful data visualizations and dashboards to communicate model performance and insights to technical and non-technical audiences.

• Integrate models into production environments with the help of MLOps and software development teams, ensuring maintainability and continuous improvement.

• Conduct feature engineering, data cleaning, and exploratory analysis to enhance model performance and reliability.

• Participate in cross-functional project reviews, providing data-driven recommendations to guide engineering decisions.

• Support the deployment and monitoring of models in cloud environments (Azure ML, Databricks), optimizing performance and scalability.

• Stay current with evolving AI technologies such as LLMs and NLP to explore novel applications in industrial analytics.

• Occasionally travel to client sites (e.g., Kuwait) for collaboration, validation, and technology deployment support.

Requirements & Eligibility:

• Strong foundation in statistics, machine learning, and data science methodologies, with proven experience analyzing real-world datasets.

• Hands-on expertise in Python (NumPy, pandas, scikit-learn, XGBoost) and fluency in SQL for data querying and transformation.

• Experience handling large, noisy, multivariate time-series data, particularly from sensors or industrial environments.

• Solid understanding of model validation, feature engineering, and performance metrics for supervised and unsupervised learning tasks.

• Excellent communication skills, with the ability to explain model insights to engineers, project managers, and stakeholders.

• Familiarity with cloud platforms such as Azure (preferred) or AWS, and ML tools like Azure ML, Databricks, or MLflow.

• Exposure to Digital Oilfield systems, production optimization, or energy analytics is an advantage.

• Knowledge of LLMs, NLP techniques, or AI-driven automation workflows is a strong plus.

• Relevant certifications such as Azure Data Scientist Associate or Microsoft AI Fundamentals are beneficial.

• Collaborative mindset and ability to thrive in cross-functional teams involving domain experts and software developers.

Expected Salary:
For Data Scientists at Luxoft working remotely from India, the average compensation typically ranges between ₹14 LPA and ₹28 LPA, depending on experience, specialization, and domain expertise. Candidates with strong oil & gas analytics experience or advanced ML/AI deployment skills may command higher packages. Luxoft offers additional benefits such as global project exposure, remote flexibility, and professional certifications to encourage continuous learning and career growth.

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