Location: Gurgaon
Work Mode: Hybrid
Experience: 3-6 Years
About Saarthee:
Saarthee is a Global Strategy, Analytics, Technology, and AI consulting company, where our passion for helping others fuels our approach, products, and solutions. Our diverse and global team works with one objective in mind — Our Customers’ Success. At Saarthee, we are passionate about guiding organizations towards insights-fueled success. That’s why we call ourselves Saarthee inspired by the Sanskrit word ‘Saarthee’, which means charioteer, trusted guide, or companion. Cofounded in 2015 by Mrinal Prasad and Shikha Miglani, Saarthee already encompasses all the components of Data Analytics consulting. Saarthee is based out of Philadelphia, USA, with offices in the UK and India.
Position Summary:
We’re expanding our Analytics & Product Data Science team and looking for Data Scientists who thrives at the intersection of data, business, and technology.
As a Data Scientist at Saarthee, you’ll be responsible for building, deploying, and scaling machine learning models and analytical solutions that drive business impact across our global clients and products. You’ll collaborate with engineering, product, and consulting teams to transform raw data into actionable insights and data-driven recommendations.
This is a high-ownership role, ideal for someone who enjoys solving complex problems, experimenting with data, and contributing to both client and product innovation initiatives.
Your Role Responsibilities and Duties:
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Design and develop predictive, prescriptive, and machine learning models using structured and unstructured data.
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Work closely with Product Managers, Data Engineers, and Business Consultants to define problems, source data, and create analytical frameworks.
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Perform data exploration, feature engineering, and hypothesis testing to identify insights and patterns.
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Build and automate end-to-end data science pipelines, from data preprocessing to model deployment.
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Collaborate with engineering teams to integrate models into production systems and analytics products.
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Evaluate model performance using statistical and business metrics, ensuring scalability and reliability.
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Communicate analytical findings through visualizations, dashboards, and presentations to technical and non-technical stakeholders.
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Stay updated on emerging AI/ML technologies, libraries, and techniques, applying them to improve existing methodologies.
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Contribute to pilot analytics and data science projects, iterating rapidly to deliver proof-of-concepts and scalable outcomes.
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Mentor junior analysts/scientists and promote data science best practices across teams.
Required Skills and Qualifications:
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Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Data Science, or related field.
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3–6 years of hands-on experience in data science, applied machine learning, or advanced analytics.
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Strong proficiency in Python and common data science libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
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Experience with SQL and working knowledge of data warehousing concepts.
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Familiarity with data visualization tools (Power BI, Tableau, Plotly, Matplotlib, Seaborn).
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Strong foundation in statistical modeling, regression, classification, clustering, and time series analysis.
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Exposure to ML Ops and model deployment on cloud platforms (AWS SageMaker, Azure ML, or GCP AI Platform).
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Understanding of data engineering workflows and ETL pipelines.
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Strong problem-solving, critical thinking, and communication skills.
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Experience working in client-facing or product-based data environments is preferred.
What We Offer:
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Bootstrapped and financially stable with high pre-money evaluation.
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Above-industry remunerations.
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Additional compensation tied to Renewal and Pilot Project Execution.
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Additional lucrative business development compensation.
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Firm-building opportunities that offer a stage for holistic professional development, growth, and branding.
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An empathetic, excellence-driven, and result-oriented organization that believes in mentoring and growing teams with a constant emphasis on learning.
