Description
Data Scientist - Time series and forecasting
Team: DS&AI Sub-CC
Location: India
Commitment: Full-time
Workplace Type: remote
Data Scientist - Time series, Forecasting
India, Remote
Growth through diversity, equity, and inclusion. As an ethical business, we do what is right — including ensuring equal opportunities and fostering a safe, respectful workplace for each of us. We believe diversity fuels both personal and business growth. We're committed to building an inclusive community where all our people thrive regardless of their backgrounds, identities, or other personal characteristics.
Tasks/ Responsibilities:
§ Work on end‑to‑end classification and forecasting use cases: problem framing, data preparation, model development, evaluation and basic deployment support (e.g. demand forecasting, churn prediction)
§ Explore and clean data; perform EDA to understand data and flag data quality issues.
§ Engineer features for tabular and time‑series data.
§ Train, validate, and tune standard ML models (e.g. logistic regression, tree‑based models, gradient boosting, simple neural nets, classical time‑series models).
§ Evaluate models with appropriate metrics that have impact on business KPIs.
§ Build clear visualizations and concise reports to present model results and insights to business stakeholders.
§ Collaborate with data engineers and AI engineers to bring models intoproduction (batch scoring, APIs, models monitoring, dashboards).
§ Document data sources, modeling assumptions, and experiment results in a reproducible way (notebooks, reports, wikis).
What We're Looking For:
Must Have:
§ Commercial experience with various classical data science and Machine Learning (ML) models (e.g. decision trees, ensemble-based tree models, linear regression etc.)
§ Knowledge of customer analytics concepts or advanced forecasting
§ Model hyperparameter tuning in an analytical role supporting business will be a plus
§ Fluency in Python, basic working knowledge of SQL
§ Knowledge of specific DS/ML libraries
§ Solid experience in one of the cloud computing platforms (Databricks or GCP or Azure)
Nice to Have:
§ Understanding of Causal machine learning
§ Experience in working with big data and distributed environments would be a plus
§ Commercial experience proven by multiple successful projects in the areas of forecasting would be a big plus
§ Experience with OOP in Python
§ Experience with MLOps
§ Familiarity with other languages R, Scala would be a plus
General:
§ Basic computer programming skills and familiarity with programming concepts
§ Strong business acumen
§ Experience with deep learning, reinforcement learning or other advanced modeling concepts in classical Data Science problems
Missing one or two of these qualifications? We still want to hear from you! If you bring a positive mindset, we'll provide an environment where you feel valued and empowered to learn and grow.
We offer:
Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites.
“Office as an option” model. You can choose to work remotely or in the office, depending on your location.
Flexibility regarding working hours and your preferred form of contract.
Comprehensive online onboarding program with a “Buddy” from day 1.
Cooperation with top-tier engineers and experts.
Unlimited access to the Udemy learning platform from day 1.
Certificate training programs. Lingarians earn 500+ technology certificates yearly.
Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly.
Internal Gallup Certified Strengths Coach to support your growth.
Grow as we grow as a company. 76% of our managers are internal promotions.
A diverse, inclusive, and values-driven community.
Autonomy to choose the way you work. We trust your ideas.
Create our community together. Refer your friends to receive bonuses.
Activities to support your well-being and health.
Plenty of opportunities to donate to charities and support the environment.
Modern office equipment. Purchased for you or available to borrow, depending on your location.
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