Total 5 Science / R&D / Research job vacancies in Bengaluru

ABOUT THIS JOB  
We won’t say we can predict the future, but our team of Market Research Analysts gets pretty close. This role combines data analysis and client consultation from the start, with plenty of room for growth. You find the stories behind scatter plots and help clients determine which products to launch. Your insights will influence decisions for some of today’s leading global companies. 

RESPONSIBILITIES 

• Managing clients and their respective projects custom research team in matters of market research based on experience in one or more sectors (Auto, financial services; media, telecom & technology, energy, etc.) 
• Reporting to a project lead, you will be responsible for the successful execution of customized quantitative studies, including project costing, questionnaire design, project management and execution, analysis and report writing. 

Client Management 

• Managing clients and their respective projects from beginning to end, including making actionable recommendations to support key business objectives 
• Consistently exceeding client expectations from project inception through completion 

Project Management 

• Successfully manage multiple projects simultaneously, all in different design/analysis stages 
• Proactively anticipating, troubleshooting, overcoming, and/or escalating challenges to your project lead in a timely manner 
• Coordinating project task activities between your project team and internal support/operations team(s) 
• Consulting (Questionnaire Design, Analysis, Reporting & Writing) 
• Assist in the development of strong and captivating proposals to meet client needs, based on short research briefs and/or elaborate RFPs; including assisting with costing structure, methodological design, analytical framework, etc. 
• Designing questionnaires/focus group screeners/interview guides to meet the specific or unique client objectives 
• Synthesis and communication of both primary and secondary research findings into actionable insights according to the client’s objectives 
• Full reporting and analysis (via PowerPoint): Interpreting and analysing multivariate data, drawing insightful conclusions and providing recommendations, where applicable. 
• Provide "in office" research, administrative and operational support to senior staff 
• Be directly accountable for work conducted for their nominated clients in terms of analyses, charting, etc and perform quality checks on all reports for alignment to request, accuracy and correctness 

A LITTLE BIT ABOUT YOU

• Proactive.
• Able to influence and persuade.
• Strong customer service and interpersonal communication skills.
• Ability to analyse and interpret data in a challenging and insightful manner.
• Strong and articulate verbal and written communication skills.
• Efficient time management, ability to multi-task and detail-oriented.
• Displays maturity and creative problem-solving skills in handling crises.
• Recommend improvements in work processes within area of responsibility.
• Analyses and interprets financial information to ensure the achievement of business targets and early identification of issues/crisis. 

We are looking for a highly analytical and dynamic Equity Derivatives Research Analyst who combines strong market knowledge with excellent communication skills. In addition to research, this role involves engaging with external stakeholders, representing the company at events, and collaborating with Key Partners in the trading ecosystem.

Key Responsibilities

● Conduct in-depth research on Crypto derivatives markets, including options and futures

● Generate trade ideas and strategies (e.g., spreads, straddles, hedging strategies)

● Analyse market trends, volatility surfaces, and macro factors impacting derivatives pricing

● Prepare daily/weekly research reports and market commentary

● Engage in conversations with Key Partners, traders, and industry experts to build insights and partnerships

● Represent Delta Exchange at industry events, conferences, and meetups

● Be open to frequent travel for events, client meetings, and ecosystem engagement

● Collaborate with marketing and growth teams for content creation, webinars, and community engagement

● Support clients/internal teams with data-driven insights and strategy explanations

• Bachelor’s or Master’s degree in Finance, Economics, Mathematics, Engineering, or related field

• Strong understanding of derivatives (Options, Futures, Greeks, volatility concepts)

• Experience with Python, R, or similar analytical tools

• Strong written and verbal communication and interpersonal skills, with the ability to engage external stakeholders

• Willingness to travel and represent the company externally

• Strong analytical thinking and problem-solving skills

Preferred Qualifications

• Experience in a trading desk, hedge fund, brokerage, or fintech/crypto environment
• Good to have experience engaging with trading communities or influencers
• Familiarity with content creation (blogs, webinars, social media insights)
• Certifications such as CFA, FRM, or NISM (India) are a plus

Key Skills

● Options Pricing & Greeks

● Volatility Modeling

● Quantitative Research

● Financial Modeling

● Stakeholder Engagement

● Public Speaking & Communication

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

Team blurb:

The GTM Data Science team operationalizes data and insights for LinkedIn’s go‑to‑market impact across Marketing, Sales, Pricing and Finance. We partner closely on multiple revenue generating initiatives. We also measure platform growth through rigorous metrics, experimentation, and enabling advanced data solutions. We organize and harmonize data at scale by building highly reliable, semantically rich data pipelines enabling data-driven decision making across the organization.

Responsibilities:

• Partner with product managers and go-to-market (GTM) teams to set up experimentation, support A/B testing, and experimentation readouts.
• Build data expertise, act as an owner for the company, and manage complex data systems for a product or group of products.
• Perform all necessary data transformations to serve products that empower data-driven decision making.
• Build and manage data pipelines, design and architect databases.
• Design, implement, integrate, and document performant systems or components for data flows or applications that power analysis at a massive scale.
• Ensure best practices and standards in the data ecosystem are shared across teams.
• Understand analytical objectives to make logical recommendations and drive informed actions.
• Be a self-starter; initiate and drive projects to completion with minimal guidance.
• Contribute to engineering innovations that fuel LinkedIn’s vision and mission.

About Trust Data Science at LinkedIn
The Trust Data Science team powers the mission of creating safe, trusted, and professional experiences on LinkedIn through rigorous metrics, experimentation, and advanced data solutions. Measuring trust is inherently challenging as abuse is adversarial, ground truth is noisy, and outcomes are often long-tailed. We tackle these challenges using advanced statistical techniques to design and build robust, actionable metrics, make them experimentable, while building highly reliable, semantically rich data pipelines enabling data-driven decision making across the Trust organization. 

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

About the role
We are hiring a senior engineering and data leader to lead our Trust Data Engineering Solutions team, a critical and strategic pillar of Trust Data Science at LinkedIn. This team owns the data foundations, platforms, and user facing tools that power Trust measurement, decision‑making, and AI‑driven workflows for the Trust R&D organization. 

This role sits at the intersection of data engineering, full‑stack development, and AI‑enabled analytics. It directly enables both human decision‑makers (data scientists, analysts, PMs, engineers and ops) and machine consumers (analytics agents, experimentation systems, ML and agentic platforms) to safely, reliably, and accurately drive data driven decisions. 

This is a high‑judgment leadership role: you will define how Trust data is produced, standardized, governed, discovered, and consumed - at scale and under real‑world constraints.

Responsibilities: What you and your team will own:

Trust data foundations

• Own the end‑to‑end strategy and evolution of Trust data foundations, including:

  • Canonical Trust metrics

  • Authoritative datasets (metrics, system data, telemetry)

  • Measurement‑critical pipelines used by Trust R&D org and external compliance reporting

• Architect and operate complex, multi‑system data pipelines spanning telemetry ingestion, transformation, ML based measurement, and serving

• Set and uphold explicit SLAs across latency, freshness, correctness, and availability, balancing speed with Trust‑grade reliability

Platform integration & ecosystem leadership

• Platformize Trust data by deeply integrating with:

  • Unified metrics and dimensional foundations

  • Experimentation and evaluation platforms

  • Analytics agents and GenAI‑enabled tooling

• Act as a technical partner and peer to trust foundations, data infra, ML infra and experimentation teams

Trust‑native tools & data democratization

• Lead the development of Trust‑native data products, including:

  • Dashboards and reporting surfaces

  • Data access APIs and services to LinkedIn wide data and agentic platforms

  • Internal data tools that lower the barrier to safe, correct data usage

• Democratize access to Trust data for analysts, data scientists, PMs, Engineers and Trust Ops, while maintaining appropriate guardrails.

• Enable agent‑based consumption of Trust data by making datasets and metrics discoverable, well‑annotated, and machine‑interpretable

Standards, governance, and context

• Establish and drive adoption of standards for telemetry, schema, metadata, and annotation across fragmented upstream systems

• Ensure Trust data carries the right context, definitions, assumptions, limitations, and lineage to support accurate retrieval and high‑stakes decisions.

People & org leadership

• Build, lead, and develop a high‑impact team of data and platform engineers

• Set a strong technical and cultural bar through architecture reviews, design rigor, and mentorship.

• Help grow senior ICs and future leaders within the Trust Data Engineering Solutions org

Key challenges your will help tackle:

• Fragmented and inconsistent Trust telemetry across multiple upstream systems

• Complex DAG orchestration with heterogeneous SLAs and dependencies

• Measurement pipelines that combine data engineering with ML models

• Making Trust data discoverable, explainable, and safe for both humans and AI agents

• Scaling platforms without sacrificing metric integrity

LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover opportunities and gain insights. Our global reach means we get to make a direct impact on the world’s workforce in ways no other company can. We’re much more than a digital resume – we transform lives through innovative products and technology.

At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.

About the team:
LinkedIn’s Trust \ team's goal is to leverage big data to empower business decisions and deliver data-driven insights, metrics, and tools in order to create a Trusted and Safe Platform, drive member engagement, business growth and monetization . With over 800 million members around the world, a focus on great user experience, and a mix of B2B and B2C programs, LinkedIn offers countless ways for an ambitious data engineer to have an impact and transform your career.

The Trust Data Science team delivers data & metrics insights, develops data platforms / tools and enables decisions at scale through inference and algorithm as part of the cross-functional Trust team to realize its mission to create safe, trusted, professional experiences where individuals and organizations can be productive and successful. In this role we are looking for a technical leader in the Trust Data Engineering and Platform team. This person will work closely with various cross-functional teams such as product, engineering, and operations to develop infrastructure and deliver tools or data structures that enable data-driven decision-making. Successful candidates will exhibit technical acumen and business savviness with a passion for making an impact by enabling both producers and consumers of data insight to work smarter.

Responsibilities

• Work with a team of high-performing data science professionals, and cross-functional teams to identify business opportunities and build scalable data solutions.
• Build data expertise, act like an owner for the company and manage complex data systems for a product or a group of products.
• Perform all of the necessary data transformations to serve products that empower data-driven decision making.
• Establish efficient design and programming patterns for engineers as well as for non-technical partners.
• Design, implement, integrate and document performant systems or components for data flows or applications that power analysis at a massive scale.
• Ensure best practices and standards in our data ecosystem are shared across teams.
• Understand the analytical objectives to make logical recommendations and drive informed actions.
• Engage with internal data platform teams to prototype and validate tools developed in-house to derive insight from very large datasets or automate complex algorithms.
• Contribute to engineering innovations that fuel LinkedIn’s vision and mission.
• Be a thought leader and modernize the data stack used by the team.