Data Scientist

Location: Pune, Maharashtra, India | Experience: Mid Level (3-5 years)

About the Company

James Darwin is a staffing company specializing in IT and software services, connecting organizations with capable professionals for technology-led business needs. We support customers across various industries by helping them strengthen engineering, analytics, and digital delivery capabilities. Our work is grounded in understanding client priorities, identifying relevant expertise, and enabling teams to execute with greater clarity and speed. The company is advancing its capabilities in cloud computing and data analytics, creating opportunities for professionals who want to work on practical, business-relevant technology problems. Headquartered in Gurgaon, we operate with a customer-oriented mindset and a focus on building dependable talent partnerships. In this role, you will contribute to client and internal outcomes by converting data into evidence, models, and decisions that improve operational performance. Your work will help establish stronger analytical foundations while supporting the broader growth of data-led services across the organization.

About the Role

As a Data Scientist, you will own the path from business question to measurable analytical outcome. You will structure ambiguous problems, prepare reliable datasets, develop and validate models, and translate findings into decisions that teams can act on. The role connects statistical reasoning, machine learning, cloud-enabled data workflows, and stakeholder communication. Success means producing analysis that is trusted, maintainable, and linked to business impact rather than isolated experimentation. You will work across customer and internal contexts, adapting methods to different industry problems while strengthening the organization’s data analytics capability.

Key Responsibilities

• Own end-to-end analytical problem solving, from framing business questions through deployment recommendations, so stakeholders receive evidence-based decisions with clear success measures and measurable operational impact.
• Build, evaluate, and improve statistical and machine learning models using disciplined validation, ensuring predictions remain reliable, explainable, and relevant to the business problem being addressed.
• Develop reproducible data preparation and feature engineering workflows that improve data quality, reduce manual effort, and create dependable inputs for analysis and production-oriented modeling.
• Partner with business, technology, and customer stakeholders to translate requirements into analytical solutions, aligning model outputs with decisions, constraints, and expected commercial or operational outcomes.
• Communicate findings through concise narratives, visualizations, and recommendations, enabling non-technical teams to understand trade-offs and take timely action based on analytical evidence.
• Monitor model and data performance after delivery, identifying drift, quality issues, or declining value so solutions can be refined before they affect business outcomes.

Essential Skills & Technologies

• Strong Python and SQL skills with practical experience in data manipulation, statistical analysis, feature engineering, and model development using maintainable, reproducible workflows.
• Working knowledge of supervised and unsupervised machine learning, experiment design, model evaluation, and statistical reasoning, with the judgment to select methods according to business context.
• Experience with data visualization and stakeholder communication, using tools such as Power BI, Tableau, or Python libraries to connect analytical findings with decisions and measurable outcomes.
• Familiarity with cloud computing concepts and data platforms, including the ability to work with scalable storage, processing, notebooks, or deployment workflows in a cloud environment.
• Proficiency in data quality assessment, documentation, version control, and collaborative development practices that make analytical work reviewable, reusable, and dependable.
• Ability to explain assumptions, uncertainty, model limitations, and recommendations clearly to technical and non-technical audiences while maintaining focus on business impact.

Additional Plus

• Experience applying analytics or machine learning to problems across multiple industries, especially where requirements are ambiguous and solutions must adapt to different operating contexts.
• Exposure to productionizing models, APIs, orchestration, monitoring, or MLOps practices that improve the reliability and sustained business value of data science solutions.
• Familiarity with modern cloud services, distributed data processing, or advanced analytics architectures that support scalable and secure delivery.

What You'll Bring

• Three to five years of hands-on experience delivering data science, advanced analytics, or machine learning solutions that move beyond experimentation into decisions, workflows, or measurable business improvement.
• A strong problem-solving orientation, with the ability to break ambiguous business needs into structured analytical questions, select appropriate methods, and define outcome measures before building solutions.
• Practical depth in Python, SQL, statistics, machine learning, data preparation, and visualization, supported by a portfolio of work that demonstrates sound reasoning and reliable implementation.
• Clear communication and stakeholder management skills, including the ability to explain technical trade-offs, challenge assumptions constructively, and make recommendations that different audiences can confidently use.
• An ownership mindset focused on data quality, reproducibility, documentation, model performance, and follow-through, ensuring analytical outputs remain useful after the initial delivery.
• Adaptability to customer and internal environments across industries, with the curiosity to learn new domains and the discipline to connect technical work to commercial or operational impact.

Why Join Us

You will join a staffing company focused on IT and software services, where data science is connected to real technology and business needs rather than treated as an isolated research function. The role offers the chance to work across varied customer contexts and help strengthen data-led capabilities for organizations with different operating models and priorities. That variety can accelerate your understanding of how analytical methods create value across industries, while building stronger judgment around problem framing, stakeholder alignment, and delivery. You will contribute to the company’s growing focus on cloud computing and data analytics, helping shape practical approaches that improve how teams use information. Your work can influence the quality of decisions, the reliability of analytical solutions, and the organization’s ability to deliver capable technology professionals to customers. Based in Pune within a company headquartered in Gurgaon, this role gives you a platform to combine technical depth with business relevance and visible ownership of outcomes.

What We Offer

• The opportunity to work on data science and analytics problems connected to IT and software services, with exposure to customer needs across varied industries and business contexts.
• A role aligned with the company’s growing focus on cloud computing and data analytics, allowing you to contribute to practical, technology-led capability development.
• A hybrid working arrangement in Pune, supporting collaboration with distributed stakeholders while preserving focused time for analytical problem solving and model development.