4.0 - 8.0 years

0 Lacs

pune, maharashtra

On-site

Conducting research aligned with the roadmaps to de-risk, mature, and incorporate advanced AI concepts into Honeywell products, focusing on the latest advancements in generative AI, causal modeling, knowledge graphs, machine learning, and deep learning techniques. Research, design, and implement scalable AI-based solutions to address high-value and complex customer challenges, thereby fostering new growth opportunities. Lead prototyping activities to support pilot programs for research and development purposes. Collaborate with cross-functional teams to devise data-driven solutions. Take ownership of problem analysis, stakeholder engagement, solution design, front-end and back-end integration, maintenance, and support of data science and analytics solutions. Develop guidelines and standards for analytics and machine learning models, their deployment, and associated processes. You Must Have: - Bachelor's/Master's degree in Engineering, Applied Mathematics, or a related field. - Strong analytics skills, including the ability to evaluate data, derive insights, and provide recommendations. - Proficiency in manipulating data sets and constructing statistical models. - Strong problem-solving skills with a focus on product development. - Chemical engineers with APC/APM experience will have an added advantage. - Experience supporting fast-paced startup engineering teams. - In-depth knowledge of the latest trends and advancements in AI and ML, particularly in generative models and LLM (both Cloud and OnPrem). - Proficiency in programming languages and libraries. - Cloud expertise in AWS and Azure. - Proficiency in languages such as Advanced Python, pySpark. - Familiarity with frameworks like Lambda, Django, Express. - Experience with databases like Postgres, Mongo, ES. - Hands-on experience in design and development, including Automated Unit testing (pyTest), with a robust technical background to create high-performance and scalable applications. - Minimum of 4 years of relevant experience in data science-related product development.,

Posted 1 month ago

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Data Scientist - Causal Inference Data Radian Technologies

7 - 12 years

25 - 40 Lacs

Hyderabad

Remote

Key Responsibilities Causal Inference & Experimentation Design and analyze experiments (A/B tests, observational studies) to identify causal relationships between variables. Apply advanced causal inference methods (e.g., propensity score matching, difference-in-differences, instrumental variables, DAGs) to estimate treatment effects. Use tools like DoWhy , CausalML , or EconML to model causal relationships. Forecasting & Multivariate Analysis Develop time-series forecasting models (e.g., ARIMA, Prophet, LSTM) to predict business metrics (sales, demand, churn). Perform multivariate regression analysis to identify key drivers of outcomes. Validate model accuracy and refine approaches based on feedback. Data Analysis & Visualization Clean, preprocess, and analyze large datasets to extract meaningful patterns. Build dashboards and reports to communicate findings to stakeholders using tools like Tableau, Power BI, or Python (Matplotlib/Seaborn). Collaboration Partner with product, marketing, and operations teams to define KPIs and design data-driven strategies. Translate complex technical results into actionable business recommendations. Technical Skills : Causal Inference : Proficiency in methods like propensity score matching, synthetic controls, and counterfactual analysis. Forecasting : Experience with time-series models (Prophet, ARIMA) and machine learning frameworks (Scikit-learn, TensorFlow). Programming : Strong Python/R skills (Pandas, NumPy, StatsModels, CausalInference). Data Wrangling : SQL proficiency for querying large datasets. Experience : 5+ years in data science, with a focus on causal inference and experimental design. Experience in industries like e-commerce, retail, or tech is a plus.

Posted 4 months ago

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