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BD is a global medical technology company that is advancing the world of health. www.bd.com
Senior ISC Data Scientist
Location
India
Posted
94 days ago
Salary
0
Seniority
Senior
Job Description
Senior ISC Data Scientist
BD
• Frame business problems into analytical and machine learning use cases. • Engineer features and develop predictive and prescriptive models. • Train, evaluate, validate, and deploy models for production use. • Monitor model performance, drift, and retraining needs. • Collaborate with Data Engineers and MLOps to ensure scalable deployments. • Automate ML workflows (CI/CD) and manage Mlflow registry. • Ensure compliance with data governance, ethical AI, and responsible AI standards. • Communicate insights, assumptions, and outcomes to business stakeholders.
Job Requirements
- 4-9 years of experience
- Strong academic or professional background in data science, statistics, or applied mathematics
- Proven experience building and deploying ML models in production environments
- Experience and knowledge of ERP, SAP systems and APS
- Experience working in cross-functional, product-oriented teams.
Benefits
- Professional development opportunities
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• Collect, organize, process, and analyze data, identifying patterns and trends that can support strategic decision-making; • Support the development of statistical analyses (descriptive and inferential); • Understand our clients' business needs by leading discussions with users and translating identified needs into requirements for development teams.
Senior Data Scientist
Cox EnterprisesCox Enterprises, a top media, communications, and automotive repair company, operates via three major divisions: Cox Media Group, Cox Communications, and Cox Au
The Insights & Advisory team at Cox Automotive is seeking a highly skilled Senior Data Scientist to lead the development of advanced analytics and AI/ML models that power innovative products and inform strategic decisions. This role blends deep expertise in statistical modeling, econometrics, machine learning, and AI acceleration with strong business acumen to deliver actionable insights for internal teams and automotive OEM clients. As a Senior Data Scientist, you will work end-to-end on analytics projects - from data preparation and model development to deployment, governance, and stakeholder communication - with emphasis on market share modeling and reporting, macroeconomic forecasting, financial modeling and engineering, and strategic analytics. You'll work independently across all phases of analytics projects, from data preparation and model development to deployment and stakeholder communication, while championing responsible AI practices and mentoring junior team members. Key Responsibilities: Advanced Analytics & AI/ML Development - Design, develop, and implement predictive, prescriptive, and optimization models using advanced statistical and machine learning techniques. - Utilize AI tools for rapid ML prototyping, automated feature engineering, and hyperparameter optimization. - Integrate AI-enhanced models into production systems and establish automated monitoring frameworks. - Apply interpretability frameworks (e.g., SHAP, LIME) and AI-driven insights to communicate results effectively. Data Analysis & Modeling - Translate business problems into analytical solutions and select appropriate methodologies. - Perform data preparation, feature engineering, and validation for large, complex datasets. - Deliver production-ready code and collaborate with engineering teams for deployment. Market, Economic, and Business Modeling - Develop and maintain methodologies for estimating and reporting market share while also building models that leverage demographic, inventory, demand, pricing, and other relevant data sources. - Create macroeconomic and business forecasting models to anticipate trends and inform strategic decisions. - Design financial models and apply advanced techniques to evaluate incentives, pricing strategies, and profitability, while remaining adaptable to emerging business needs and diverse datasets. Strategy and Internal Consulting - Serve as an internal consultant, framing business problems and aligning solutions with strategic objectives. - Facilitate decision-making using structured approaches; leverage negotiation and conflict resolution skills to drive consensus. Data Engineering & Governance - Own data preparation, feature engineering, validation, and production-ready code in Python and SQL. - Partner with engineering to integrate models, automate monitoring, and ensure reliability. - Establish responsible AI practices including bias detection, interpretability, and compliance monitoring. Collaboration, Leadership & Communication - Partner with product, engineering, and business stakeholders to align models with strategic goals. - Present findings and recommendations clearly to both technical and non-technical audiences. - Mentor junior staff, contribute to team capability building, and engage in thought leadership. Minimum Qualifications: - Bachelor's degree in Statistics, Econometrics, Operations Research, Applied Mathematics, Computer Science, Economics, or a related quantitative field and 4 years' experience in a related field. The right candidate could also have a different combination, such as a master's degree and 2 years' experience; a Ph.D. and up to 1 year of experience; or 16 years' experience in a related field - Proven experience applying descriptive, predictive, and prescriptive analytics to real-world business problems. - Strong background in statistics and econometrics, including panel data analysis, time series modeling, and causal inference. - Hands-on experience with market share modeling and reporting. - Experience in macroeconomic forecasting and financial modeling/engineering. - Proficiency in Python and SQL, with ability to deliver production-quality code and manage the full ML lifecycle. - Experience with AWS or other cloud platforms and collaboration with engineering teams for deployment. - Ability to integrate models into enterprise systems and maintain production-ready code. - Experience operating as an internal consultant within a complex enterprise environment. - Exceptional communication and problem-solving skills. Preferred Skills - Advanced statistical techniques: GL GLMs, time series, forecasting, clustering, PCA; causal and panel methods. - Optimization methods: linear/mixed integer programming, heuristic approaches, network flow. - ML frameworks: scikit learn, TensorFlow, PyTorch; model interpretability with SHAP and LIME. - Experience with data visualization tools (Tableau, Power BI) and compelling storytelling. - Knowledge of CI/CD pipelines, data governance, and Agile methodologies. - Market share modeling approaches: discrete choice, multinomial and nested logit, demand elasticity. - Financial engineering: risk models, Monte Carlo, scenario analysis, option style incentive evaluation. - AI accelerated development and agentic frameworks; CI/CD and Agile delivery. - Data visualization and storytelling with Tableau or Power BI. - Evidence of peer reviewed publications or conference presentations. Why Join Cox Automotive? At Cox Automotive, data science drives innovation. As a Sr Data Scientist, you'll shape the future of AI-powered analytics, deliver impactful insights, and mentor the next generation of data talent, all while working in a collaborative, forward-thinking environment. USD 101,500.00 - 169,100.00 per year Compensation: Compensation includes a base salary of $101,500.00 - $169,100.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate's knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program. Benefits: The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company's needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave. Application Deadline: 03/19/2026
• Manage a team of 19, including multiple people managers • Work with C-Suite/VP level stakeholders to set roadmaps for your team and influence the company’s product roadmap and overall strategy • Review key deliverables to ensure quality and perform ad-hoc analyses when particularly complex and important • Creatively answer questions nobody is asking but that help us improve how we run our business • Create KPIs that measure the health of our product and its impact on our customers • Assist the sales and marketing teams in creating product impact claims for major deals • Mentor and grow your teammates to deliver strong deliverables across the business • Set a technical strategy for your team that uses the latest technologies while balancing immediate execution with long term vision • Work with our data engineering team to help create data marts that allow for self service and accelerate our speed to value over time
• Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring. • Build foundational modeling to drive SentiLink’s expanding suite of Fraud and Financial Risk products. • Research new types of fraud and develop new SentiLink products around identity verification. • Achieve success by researching / developing through iteration, integration of new data sources and inventive feature engineering. • Write production-ready code that can be relied on for real-time decision making by our partners. • Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts. • Work with engineering, risk operations, and data acquisitions to access necessary data, maintain data quality, and support data access




