Job description
Position: Data Scientist
Location: Mumbai
About LRN:
LRN is the world’s leading dedicated ethics and compliance SaaS company, helping more than 30 million people every year navigate complex regional and global regulatory environments and build ethical, responsible cultures. With over 3,000 clients across the US, EMEA, APAC, and Latin America—including some of the world’s most respected and successful brands—we’re proud to be the long-term partner trusted to reduce organizational risk and drive principled performance.
Named one of Inc Magazine’s 5000 Fastest-Growing Companies, LRN is redefining how organizations turn values into action. Our state-of-the-art platform combines intuitive design, mobile accessibility, robust analytics, and industry benchmarking—enabling organizations to create, manage, deliver, and audit ethics and compliance programs with confidence. Backed by a unique blend of technology, education, and expert advisement, LRN helps companies turn their values into real-world behaviors and leadership practices that deliver lasting competitive advantage.
About the role:
We’re looking for a curious, hands-on, and impact-oriented Data Scientist to join our team. You’ll work across a wide range of structured and unstructured data to support decision-making, build models, and explore how generative AI can enhance our products and workflows.
You don’t need decades of experience — we value initiative, strong fundamentals, and a desire to learn over perfect resumes. This is a great opportunity for someone early in their career who wants to shape meaningful applications in AI, analytics, and real-world business challenges.
What you’ll do:
- Work with cross-functional teams to understand business problems and translate them into data science tasks.
- Analyze structured and unstructured data (e.g., text, course interactions, HRIS data, survey responses, logs) to surface insights and patterns.
- Build predictive and descriptive models using machine learning and statistical techniques.
- Experiment with generative AI (LLMs, embeddings, prompt engineering, fine-tuning) to explore new capabilities.
- Collaborate with data engineers, product managers, and designers to turn models into production-ready features.
- Communicate findings through visualizations, dashboards, and clear storytelling
What we’re looking for:
Core Skills
Ability to take initiative in identifying new opportunities where data science or AI can drive value — even in loosely defined or ambiguous problem spaces.
Solid grasp of data wrangling, EDA, and basic statistical modeling.
Comfort working with SQL and exploring data in relational databases.
Experience working with Python and common libraries (pandas, numpy, etc.).
Familiarity with a subset of standard modeling techniques such as:
Logistic regression, decision trees, random forests, gradient boosting (e.g., XGBoost, LightGBM)
Clustering (K-Means, DBSCAN)
Text vectorization (TF-IDF, word embeddings, sentence transformers)
Dimensionality reduction (PCA, t-SNE, UMAP)
·
Generative AI & ML
- Familiarity with large language models (e.g., OpenAI, Hugging Face, etc.).
- Experience using embeddings, vector databases, or prompt-based pipelines.
- Interest or experience in fine-tuning or evaluating generative models.
Mindset & Collaboration
- Eagerness to learn and apply new tools, techniques, and frameworks.
- Ability to work independently and push through ambiguity.
- Strong communication skills and a collaborative spirit.
- Comfortable receiving feedback, iterating fast, and delivering value.
Nice-to-Have Extras
- Experience with data visualization tools (e.g., Plotly, Dash, Tableau, Streamlit).
- Exposure to model monitoring, ML Ops, or data pipelines.
- Interest in ethics, compliance, education, or B2B SaaS domains.
- Familiarity with cloud platforms like AWS or GCP.
Excellent medical benefits, including family plan
Paid Time Off (PTO) plus India public holidays
Competitive salary
Combined Onsite and Remote Work
LRN is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
