Senior Data Science & AI Specialist

Posted 23 Days Ago
Be an Early Applicant
Bangalore, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Robotics • Analytics • Energy
The Role
Develop and operationalize machine-learning forecasting models for financial metrics, including revenue, costs, and cash flow. Own the ML lifecycle from feature engineering through deployment and monitoring, apply time-series and classical ML methods, and use explainability techniques such as SHAP. Serve as product owner for forecasting data products, create dashboards and reports, analyze prediction variances, and translate model outputs into actionable insights for Finance, Sales, and management stakeholders.
Summary Generated by Built In

At ABB, we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world.

This Position reports to:

Data Analytics & BI Manager
 

Your role and responsibilities:
In this role, you will have the opportunity to develop end-to-end business intelligence framework for online products and SAAS solutions based on requirements that include recommending an appropriate architecture (on-premises/cloud), analytics, and reporting. Each day, you will evaluate business data to produce meaningful insights and metrics and to identify trends that could improve business performance. You will also showcase your expertise by designing new dashboards using best practices and intuitive visualization.
The work model for the role is: # LI Hybrid
This role is contributing to the AUMA Business in Bangalore Location.
You will be mainly accountable for:

  • Design, develop, and operationalize ML-driven models to forecast revenue, costs, cash flow, and other key financial metrics — owning the complete ML lifecycle from data preparation and feature engineering through deployment and monitoring

  • Explore and implement forecasting and scenario analysis approaches (classical ML, time series methods, statistical techniques, etc) to optimize accuracy, explainability, and operational feasibility

  • Product Owner for Forecasting: define and own the product vision, roadmap, and backlog for forecasting data products, ensuring alignment with business strategy and stakeholder needs

  • Perform feature importance and driver analysis to identify key factors influencing financial outcomes as well as apply model explainability techniques to build stakeholder trust in predictions

  • Translate model outputs into actionable insights for Finance, Sales, and other Management Functions

  • Develop dashboards and automated reports to track accuracy and financial performance over time

  • Conduct root-cause analysis on variances between predicted and actual outcomes, and recommend corrective actions

  • Facilitate cross-functional engagement with business stakeholders to refine forecasting assumptions and validate model outputs

Qualifications for the role (Mandatory):

  • Degree in B.Tech / M.Tech / BCA / MCA (Computer Science, Data Science, Statistics, or related field).

  • 5-7 years of hands-on experience in driving forecasting and predictive analytics solutions using AI/ML techniques in a business or finance environment

  • Strong, demonstrated expertise in traditional time series methods (ARIMA, SARIMA, Exponential Smoothing, etc.) and classical ML algorithms (regression models, XGBoost, Random Forest, LSTM).

  • Proven experience managing the complete ML lifecycle — from data pipeline design and feature engineering through model training, validation, deployment, and performance monitoring. Hands-on experience with feature importance/driver analysis and model explain ability techniques (SHAP analysis or equivalent).

  • Advanced proficiency in Python and SQL for data manipulation, modeling, and statistical analysis. Strong experience with ML frameworks such as Scikit-learn, TensorFlow, PyTorch, or equivalent.

  • Strong statistical knowledge including hypothesis testing, regression analysis, and model validation techniques. Experience with data visualization tools (Power BI, Streamlit, Python libraries like Plotly, Matplotlib).

More about US:

ABB a provides a comprehensive range of integrated automation, electrical and digital systems and services for customers in the process, hybrid and maritime industries. These offerings, coupled with deep domain knowledge in each end market, help to optimize productivity, energy efficiency, sustainability and safety of industrial processes and operations.

Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative. We welcome people from all backgrounds and experiences.

Ready to make an impact? Apply today or visit www.abb.com to learn more about the impact of our solutions across the globe.

Recruitment Fraud Warning

ABB never asks for payment from job applicants. All genuine job offers follow a formal application and interview process.

View current job openings and apply at: https://careers.abb/global/en/home

For more information, read our full fraud warning notice at: https://global.abb/group/en/careers/how-to-apply/fraud-warning

Skills Required

  • Degree in B.Tech, M.Tech, BCA, or MCA in Computer Science, Data Science, Statistics, or a related field
  • 5-7 years of hands-on experience developing forecasting and predictive analytics solutions using AI/ML techniques in a business or finance environment
  • Expertise in traditional time-series methods, including ARIMA, SARIMA, and Exponential Smoothing
  • Experience with classical ML algorithms, including regression models, XGBoost, Random Forest, and LSTM
  • Experience managing the complete ML lifecycle, including data pipeline design, feature engineering, training, validation, deployment, and performance monitoring
  • Experience with feature importance, driver analysis, and model explainability techniques such as SHAP
  • Advanced proficiency in Python and SQL for data manipulation, modeling, and statistical analysis
  • Strong experience with ML frameworks such as Scikit-learn, TensorFlow, PyTorch, or equivalent
  • Strong statistical knowledge, including hypothesis testing, regression analysis, and model validation techniques
  • Experience with data visualization tools such as Power BI, Streamlit, Plotly, or Matplotlib

ABB Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about ABB and has not been reviewed or approved by ABB.

  • Healthcare Strength — Healthcare coverage is described as comprehensive, with medical, dental, vision, mental health support, and disability and life insurance included. Immediate eligibility in some roles reinforces the sense of dependable core coverage.
  • Leave & Time Off Breadth — Time-off offerings are described as broad, including paid holidays, sick days, volunteer time, sabbaticals, and, in some cases, 25 days of PTO. Flexible scheduling and remote-work options add to perceived time-off and flexibility value.
  • Retirement Support — Retirement benefits are positioned as robust, including a 401(k) with company contributions or matching and, in some cases, profit sharing or pension savings. Stock purchase/share acquisition programs complement longer-term savings options.

ABB Insights

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The Company
HQ: Zürich
104,000 Employees
Year Founded: 1988

What We Do

ABB is a leading global technology company that energizes the transformation of society and industry to achieve a more productive, sustainable future. By connecting software to its electrification, robotics, automation and motion portfolio, ABB pushes the boundaries of technology to drive performance to new levels. With a history of excellence stretching back more than 130 years, ABB’s success is driven by about 110,000 talented employees in over 100 countries. www.abb.com

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