Consultant Data Science jobs at Dell in India

Data Science Senior Advisor MMX

As a Data Science Senior Advisor, you will be responsible for contributing to business strategy and influence decision making based on information gained from deep dive analysis. You will produce actionable and compelling recommendations by interpreting insights from complex data sets. You will design processes to consolidate and examine unstructured data to generate actionable insights. You will also partner with business leaders, engineers and industry experts to construct predictive models, algorithms and probability engines.
You will:

• Gather and preprocess marketing data from various sources such as cloud based/ on-premise databases ensuring data quality and consistency
• Design and implement Bayesian Marketing Mix Models to estimate the incremental impact of marketing and media channels on business KPIs
• Develop priors and leverage hierarchical Bayesian frameworks to model data across geographies, products, and time.
• Create visualizations to present data findings in a clear and actionable manner.
• Work with cross-functional teams, including go to market teams, data platform team to implement data-driven solutions.
• Creating and maintaining custom built libraries.
• Maintaining version control of artifacts (Github)

Essential Requirements

• Hands-on experience building marketing mix models, with a strong understanding of marketing performance measurement.
• Strong proficiency in Python, R tidyverse and SQL
• Familiarity with cloud platforms such as GCP, Data bricks
• Reproducible artifact building (Rmarkdown, Notebooks)

Desirable Requirements

• Experience with machine learning algorithms and their application in marketing.
• Excellent communication skills to convey complex data insights to non-technical stakeholders.
• Understanding of marketing operations and how data can drive decision-making.
• Ability to think critically and solve complex problems with attention to detail

2025

Senior Consultant, Product Management (AI/Agentic)

Join our Product Management team to shape the next generation of AI + Digital transformation and enabling Service Modernization 2.0 as a Product Management Senior Consultant iWith clear visibility into how Digital Products contribute to broader modernization goals. You’ll define strategy, lead delivery, and ensure safe, measurable outcomes across the product lifecycle.

As a Senior Consultant, you will identify high-impact AI opportunities, design the North Star experience, and deliver products that align with business goals. You’ll partner with Engineering, Design, and Operations to build integrated roadmaps and execute responsibly.

Key responsibilities

• Define strategy and roadmap for agentic AI capabilities tied to clear outcomes.
• Design and validate the North Star experience through prototypes and testing.
• Ensure responsible product delivery with governance guardrails and strong observability.
• Quantify impact and own product metrics (adoption, NPS, cost savings) against OKRs.
• Collaborate cross-functionally to manage dependencies and drive execution in Agile frameworks.

• 15-18 years in product management or related roles, including 3+ years in AI/ML-powered products.
• Proven ability to define long-term vision, write PRDs/user stories, and lead end-to-end delivery.
• Strong technical acumen: architecture, data, model integration, evaluation, and safety.
• Analytical mindset with experience in product analytics and experimentation.
• Executive-level communication and stakeholder management.

Preferred

• Bachelor’s degree or equivalent experience.
• Familiarity with cloud, edge, compute, storage, networking, and security domains.

You will:

• Collect and analyze linguistic data; implement core NLP techniques like tokenization, NER, and sentiment analysis for MT/NLG pipelines.
• Design reproducible experiments, establish annotation protocols, and evaluate models using metrics like BLEU, COMET, and ROUGE.
• Build and enrich knowledge graphs; design ontologies and schemas; optimize queries using SPARQL and Cypher.
• Develop GraphRAG pipelines, train graph/text embeddings, and integrate agentic frameworks (e.g., LangGraph) for multi-hop reasoning and query translation.
• Work with MLOps teams to deploy models with CI/CD; monitor GenAI solutions for quality and performance; communicate results to stakeholders.

Essential Requirements

• Strong Python skills with hands-on experience in ML frameworks (PyTorch, TensorFlow) and data processing libraries.
• Deep understanding of NLP techniques (e.g., summarization, paraphrasing, NER, sentiment analysis) and evaluation metrics (BLEU, COMET, ROUGE, METEOR).
• Familiarity with LLM frameworks (LangGraph, LlamaIndex), RAG design patterns, and multi-agent orchestration with human-in-the-loop processes.
• Skilled in graph ML, embeddings, and semantic modeling; experienced in building GraphRAG pipelines and applying graph algorithms.
• Excellent communication and presentation skills; ability to document and explain complex solutions clearly.

Desirable Requirements

• Experience with Agile development methodology (e.g., Scrum)
• Experience - 12 to 15 yrs

As a, you will be responsible for contributing to business strategy and influence decision making based on information gained from deep dive analysis. You will produce actionable and compelling recommendations by interpreting insights from complex data sets. You will design processes to consolidate and examine unstructured data to generate actionable insights. You will also partner with business leaders, engineers and industry experts to construct predictive models, algorithms and probability engines.

You will:

• LLM//Agentsandtraditional AI/ML

• Build prototypes and scalable AI/ML solutions that will be integrated into software productsC

• Lead more junior data scientistandCollaborate with software engineers, business stakeholders and product owners in an Agile environment

• Have complete ownership of model outcomes and drive continuous improvement

Essential Requirements

• Proficient withwriting sophisticated, clean, andobject orientedPythoncodeStrong background in math, statistics, andmachine Learning knowledge (deep learning, NLP,classification,forecasting,regression)

• Professional experience in ML model deploymentin production

• Ability to work with internal stakeholders to transfer business questions intodata scienceproblem statements

• Ability to effectively communicate data science progress to non-technical internal stakeholders.

• Ability toplay the technicallead/ architect role for

Desirable Requirements

• Master’s or PhD in a quantitative discipline.

• Professional experience with LLM/Agentic technologies

You will:

• Architect and influence the shaping of future products by providing mechanical engineering insight into the technology roadmap.
• Identify and scope projects around innovation opportunities as well as technology risks.
• Execute designs for complex systems backed by thorough engineering analysis. Take responsibility for gathering requirements and concepts generation.
• Engage ODM partners and technology providers to gather information and release requirements.
• Generate IP to protect innovation.

Essential Requirements

• Bachelor’s Degree in Mechanical Engineering with 14+ years of work experience in design of mechanical electrical device or product. Extensive experience in designing complex electro-mechanical assemblies with an expert understanding of material properties, structure design, shock and vibration requirement, tolerance analysis, electro-mechanical layout and placement, thermal design concept, and system integration.
• Possess strong communication skills (written and oral) with other company team members and the customer as required and have experience speaking and influencing at an executive level.
• Have extensive experience with CAD tool (CAD experience required).
• Familiar with mechanical parts manufacture process and good relationship with industry key technical provider.
• Possess working knowledge of mass-production manufacturing processes and material costs.

Desirable Requirements

• Master’s Degree in Mechanical Engineering
• Experience with thermal engineering and electrical engineering

As a Data Science Advisor, you will be responsible for contributing to business strategy and influence decision making based on information gained from deep dive analysis. You will produce actionable and compelling recommendations by interpreting insights from complex data sets. You will design processes to consolidate and examine unstructured data to generate actionable insights. You will also partner with business leaders, engineers and industry experts to construct predictive models, algorithms and probability engines.
You will:

• Play a key role in designing and implementing intelligent solutions using Generative AI, Large Language Models (LLMs), and Machine Learning and work closely with senior architects and cross-functional teams to bring AI-driven innovations to life, particularly in the domain of technical support services and enterprise automation.
• Contribute to the design and development of GenAI and LLM-based solutions for enterprise-scale use cases and collaborate with senior data scientists and engineers to build, fine-tune, and deploy NLP and deep learning models.
• Assist in the integration of AI models into existing systems and workflows, ensuring performance and scalability and participate in data preparation, feature engineering, and model evaluation for various AI/ML projects.
• Stay updated on the latest trends in AI/ML, LLMs, and MLOps, and bring innovative ideas to the team and support the monitoring and optimization of deployed models using MLOps tools and best practices.

Essential Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field.
• 4–8 years of hands-on experience in data science, machine learning, or AI solution development.
• Proficiency in Python, with experience in libraries such as TensorFlow, PyTorch, or Hugging Face Transformer and Familiarity with LLMs, NLP techniques, and Generative AI frameworks.
• Experience working with cloud platforms (AWS, Azure, or GCP) and containerization tools like Docker.
• Strong analytical, problem-solving, and communication skills.

Desirable Requirements

• Exposure to MLOps tools (e.g., MLflow, Kubeflow, SageMaker) and model lifecycle management and understanding of data engineering concepts and tools like Spark, Kafka, or Airflow.
• Experience with REST APIs, microservices, and integrating ML models into production environments and knowledge of DevOps practices, CI/CD pipelines, and Kubernetes is a plus.
• Ability to work in agile teams and contribute to multiple projects simultaneously.

Application closing date:

You will:

• Drive innovation and strategic prioritization by identifying differentiated security features through market and competitive analysis, aligning initiatives with business goals, and championing capabilities that advance our data protection offerings.
• Lead cross-functional product execution by partnering with engineering, sales, channel partners, and customers to define security requirements and deliver impactful, customer-centric solutions.
• Leverage deep technical acumen to engage in architectural and functional design discussions, evaluate trade-offs, challenge assumptions, and assess security risks associated with key decisions.
• Act as the Data Protection Security subject matter expert, supporting field teams and customers with clear guidance, documentation, and advocacy around product capabilities, strengths, and limitations.
• Coordinate urgent security incident responses with urgency and precision by collaborating with Engineering, Legal, Support, Communications, and incident response teams to ensure effective resolution of high-impact vulnerabilities.

Essential Requirements

• 5+ years of Product Management experience, or equivalent experience in engineering, support, or technical sales within the enterprise data protection and/or security domain.
• End-to-end technical expertise in security and data protection, including encryption (in-flight and at-rest, key management), identity and access management (LDAP/AD, SSO, SAML, OIDC, OAuth 2.0, MFA, RBAC/ABAC), PKI, CA certificates; and security best practices for OS, containerized, and cloud environments (Linux, Kubernetes, AWS, Azure, etc.).
• Proven ability to create and maintain a prioritized product roadmap, communicate it effectively to stakeholders, and adapt based on market feedback and business needs.Expertise in evaluating and prioritizing competing product opportunities and features using established frameworks, with strong decision-making skills that balance business value, technical feasibility, and resource constraints.
• Strong analytical and communication skills, with the ability to translate customer needs, product usage data, and market trends into actionable insights, while aligning cross-functional teams and building productive stakeholder relationships.

Desirable Requirements

• Familiarity with modern security ecosystems (SIEM, SOAR, XDR, MDR), third-party security integrations, and regulatory frameworks (CRA, DORA, NIS2, SOC 2, APL, FIPS). Understanding of the impact of AI on security and data workflows, including anomaly detection, predictive threat intelligence, and AI/ML platform integration.
• Experience with go-to-market strategy execution including product positioning, pricing, messaging, launch planning, and sales enablement; proven bias for action and ownership mentality in driving cross-functional initiatives and product success.