Data Science Manager Salary India in Toronto

Position: Project Management Analyst (PMO) Location: Toronto, ON Work Arrangement: Hybrid – 4 days per week in office (office in downtown Toronto) Salary: $57,000 About mthree: Since 2010, mthree has been helping clients solve their business and technological challenges. We are a technology and business consultancy with a global workforce delivering significant business and IT projects in some of the largest financial services organizations worldwide. Core Services Consulting and Advisory Managed Services Alumni Graduate Program Alumni Pro Program We have a global presence and are experts in delivering exceptional quality to our client base, providing consulting services across Risk, Regulation & Compliance; Vendor Products; Application Support; Application Development; Cyber & Information Security; Data Science and DevOps areas. Our alumni program offers experienced professionals access to top roles in tech, finance, aviation and insurance. Join us to work on groundbreaking technology projects, from international trading platforms to critical applications for leading airlines. We recruit professionals who are eager to fast-track their careers in technology or operations within prestigious

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data Science & Analytics is at the heart of Lyft's products and decision-making. The Rider Experience team sits at the center of how millions of riders discover, choose, and return to Lyft. We are hiring a Data Science Manager to lead our Toronto-based science & analytics team that turns rider behavior into product strategy. This role owns the analytical foundation behind our most consequential rider-facing decisions: how we measure experience quality, where friction costs us retention, and which bets move rider LTV. You will set the measurement and experimentation standards for rider product squads, and translate ambiguous business questions into rigorous, decision-ready analysis that shapes roadmap and investment. You will also lead the team's transition to AI-native data science and analytics workflows, embedding AI tooling into how we explore data, make decisions, and ship products. Responsibilities: Lead and grow a high-performing team of data scientists and analysts with diverse backgrounds Define and drive the data science vision, strategy, and roadmap, aligning with business and product objectives to improve market competitiveness and rider experience Provide strong technical guidance and coaching to the team on complex data science problems Champion data-driven decision-making and prioritization by partnering with product managers, engineers, marketers, and leaders to translate insights into decisions and action Lead deep-dive analyses into large-scale datasets to identify opportunities for improving rider app experience and overall rider product health Ensure robust experimentation and causal inference methodologies are applied to measure the impact of new features and strategies Mentor and guide the professional and technical development of your team members; help develop the

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data and analytics are at the heart of Lyft's products and decision-making. The Metrics team sits in the Central Market Management organization and owns the business metrics that leaders use to run the marketplace. We define these metrics, build and manage the tools and dashboards that make them reliable and easy to access, and drive consistent, standardized definitions across the organization. We are looking for a Data Scientist to join the Metrics team and help shape Lyft's products and decision-making. You will own a domain within the team's surface area, building and maintaining the data and metrics that leaders and partner teams rely on, with significant executive exposure along the way. We want an intellectually curious person with strong attention to detail, a track record of analytical problem-solving, and skilled communication. You will report to a Data Science Manager. Responsibilities Own one or more domain datasets end-to-end, from source data through to the metrics that consumers rely on Build and maintain the processing logic and pipelines that turn raw inputs into trusted, analysis-ready data Own the business metrics derived from that data, developing the deep understanding of the source needed to build each metric correctly Ensure the data is accurate, consistent, and reliable, with quality checks that catch problems before consumers see them Deliver data and metrics to stakeholders in a usable form, and support them as they integrate it into their decisions Partner with product managers, engineers, and operators to translate the data into decisions and action Communicate findings to stakeholders in a clear and concise manner Experience Degree in a quantitative field such as statistics, economics, applied math, operations research, or engineering (advanced degrees preferred), or relev

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for Masters or PhD students who are passionate about solving mathematical problems with data and are excited about working in a fast-paced, innovative and collegial environment. We are hiring for a variety of Data Science interns, focusing on the following specialties: Optimization: Construct and fit statistical or optimization models that facilitate automated decision making in the app. Machine Learning: Design, build, tune, and deploy machine learning models with a special emphasis on feature engineering and deployment. Inference: Design and analyze tests in our dynamic marketplace, estimating statistical and ML models to enable better decisions, and developing and evaluating algorithmic policies in our pricing, dispatch, and incentives systems. You will report into a Science Manager. Responsibilities: Partner with Engineers, Product Managers, and other cross-functional partners to frame problems, both mathematically and within the business context Perform exploratory data analysis to gain a deeper understanding of the problem Write production modeling code; collaborate with software engineers to implement algorithms in production Design and run both simulated and live traffic experiments Analyze experimental and observational data; communicate findings including working with partner teams and presentations; facilitate launch decisions Experience: Currently pursuing a Masters or PhD degree at a university in Canada (required) in mathematical sciences ( Opera

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft connects people to transportation to change the way we live and get around our communities. We are looking for product managers who bring exceptional creative and analytical skills to drive forward a best in class product. Product management at Lyft leads the integration of engineering, data science, and design to achieve the company's vision for reinventing transportation. We are looking for entrepreneurial and passionate Product Managers to innovate and execute across a rapidly growing, fast paced company and industry from our Toronto office. Every great support experience depends on the person behind it having the right tools, context, and intelligence to solve the problem in front of them. The Platform & Data teams build the tools our human support agents work in every day—and own the data that tells Lyft, and the world, what our customers are actually experiencing. As AI rapidly changes what's possible, we're reinventing how agents work: pairing them with copilots and AI that surface the right answer instantly, take on repetitive work, and raise the quality and consistency of every interaction. At the same time, we're building the data foundation that turns millions of support contacts into an accurate, trusted view of issue types and trends—used inside the team, across the company, and in what we report externally. This role owns that mandate end to end: setting the vision and strategy, and driving execution on the hardest problems across both the platform and its data. Responsibilities: Own the vision, strategy, and multi-quarter roadmap for Lyft's agent platform and the data that powers customer care & safety reporting Define and drive how AI and copilot capabilities make agents more efficient and raise the quality and consistency of their work Lead execution on the most complex,

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. On the Rider team, we are growing our team with people who want to enrich the lives of our community through technology. You'll collaborate with highly cross-functional teams such as Product, Design, Data science, and Analytics, as well as other organizations like Driver, Partners, and Marketplace, to deliver on that promise. As the Senior Engineering Manager for the Rider Loyalty, Partnerships, and Rider Pay (PLP) group, you will lead multiple managers and Staff ICs with end-to-end teams, consisting of iOS, Android, and Server, to make Riders into Members and to build a robust network of partners that our Riders love. It is your responsibility to sweat the details by being customer-obsessed with specific Rider needs and to build innovative product solutions to address them. Responsibilities: Set the technical vision and team strategy for the PLP group and communicate that downwards, with peers, and upwards with ELT Coach and guide an organization of managers and engineers in their people and technical development Collaborate with cross-functional stakeholders to deliver high business impact Work closely with the Lyft recruiting team to hire high-potential candidates from diverse backgrounds Experience: BS/MS or equivalent in Computer Engineering, Computer Science, or a related field, or relevant work experience 3+ years of experience managing engineering teams of 20+ members, including teams across iOS, Android, and Server platforms, as well as experience in managing managers Ability to thrive in a heavily cross-functional environment and drive projects to completion regardless of the organizational structure Passion for building scalable and extensible solutions that enable others and ensure a high-quality product Experience launching and supporting consumer-facing products at scale Strong technica

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Rider Loyalty team is where riders become members. We build the membership, rewards, and benefits products that give people a reason to choose Lyft on every trip, and we make sure the value a rider has earned shows up at the moment it matters. Loyalty sits inside the Rider Loyalty, Partnerships, and Rider Pay (PLP) group. You will lead a team of engineers across iOS, Android, and Server. You will own the membership and rewards platform end to end and work daily with Product, Design, Data Science, and Partnerships. Responsibilities: Own the Loyalty roadmap from strategy through delivery. Turn goals like member growth and retention into an engineering plan, and manage the dependencies that run through Partnerships and Rider Pay. Build and scale the systems behind membership, rewards earning and redemption, and benefit delivery. Hold a high technical bar through architecture reviews, tech debt management, observability, reliability, and on-call. Grow engineers by matching people to the right opportunities, setting clear expectations, and giving feedback early. Experience: 5+ years building software professionally, including 2+ years directly managing engineers. You have managed a team that shipped both mobile and backend work, and you can still read and review code in at least one of those areas. You have owned a consumer product used by millions of people each month. You use AI tools in your own work and have a clear view of where they help and where they do not. BS/MS in Computer Science, Computer Engineering, or a related field, or equivalent practical experience. Benefits: Extended health and dental coverage options, along with life insurance and disability benefits Mental health benefits Family building benefits Child care and pet benefits Access to a Lyft funded Health Care Savings Accou

Upwork Inc.'s (Nasdaq: UPWK) family of companies connects businesses with global, AI-enabled talent across every contingent work type including freelance, fractional, and payrolled. This portfolio includes the Upwork Marketplace, which connects businesses with on-demand access to highly skilled talent across the globe, and Lifted, which provides a purpose-built solution for enterprise organizations to source, contract, manage, and pay talent across the full spectrum of contingent work. From Fortune 100 enterprises to entrepreneurs, businesses rely on Upwork Inc. to find and hire expert talent, leverage AI-powered work solutions, and drive business transformation. With access to professionals spanning more than 10,000 skills across AI & machine learning, software development, sales & marketing, customer support, finance & accounting, and more, the Upwork family of companies enables businesses of all sizes to scale, innovate, and transform their workforces for the age of AI and beyond. Since its founding, Upwork Inc. has facilitated more than $30 billion in total transactions and services as it fulfills its purpose to create opportunity in every era of work. Learn more about the Upwork Marketplace at Upwork.com and follow us on LinkedIn , Facebook , Instagram , TikTok , and X ; and learn more about Lifted at Go-Lifted and follow on LinkedIn . Upwork's Match Platform team sits at the heart of how clients and freelancers find each other. As Senior Product Manager for Match Platform, you will own the shared infrastructure that powers matching, personalization, embeddings, and evaluation across multiple product surfaces. This is a high-leverage role: the models, features, and frameworks you build become the foundation that other product and ML teams build on. You will partner closely with engineering, data science, machine learning, analytics, and marketplace operations to reduce duplication, increase reuse of shared capabilities, and drive measurable improvem

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft connects people to transportation to change the way we live and get around our communities. We are looking for a Senior Staff Technical Program Manager who brings exceptional technical and analytical skills to drive execution across high-impact product initiatives. Come be part of a team at Lyft focused on enabling and empowering engineering teams to deliver at scale. Technical Program Managers at Lyft drive cross-functional initiatives, leveraging strong leadership, planning, communication, and collaboration skills. Our TPMs are technically strong with deep product and software engineering experience. They are problem solvers who make things happen by setting clear goals and inspiring teams to deliver. TPMs at Lyft are both strategic and tactical, doing what it takes to successfully deliver top-priority programs that have a material impact on the business. This role will support product-facing teams within Rideshare, focusing initially on the Partnerships, Loyalty and Payments organization, where you will be responsible for helping them to create a singular loyalty offering that is accessible, emotional, rewarding, and which makes it simple to choose Lyft. You will collaborate with engineering, product, data science, design, analytics, and operations to drive iterative delivery that delights our riders and drivers. Responsibilities Lead cross-functional product initiatives from ideation through planning, execution, launch, and post-launch — ensuring alignment, accountability, and measurable outcomes at every phase. Provide hands-on support across all phases of the software development lifecycle, including project planning, resource allocation, progress tracking, risk mitigation, KPI ownership and measurement, and leadership communications. Partner with engineering, product, data science, design

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve identifying and scoping opportunities, shaping team priorities, recommending and implementing technical solutions, designing experiments, and measuring the impact of new features. The Airports team, within the Driver organization, focuses on the airport marketplace and the unique products designed for this use case. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experience and have unique dynamics. As a Data Scientist on the Airport team, you will collaborate with our team of engineers, product managers, and designers to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product changes, develop end-to-end technical solutions, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as: What rider segments are present at airports and how can we address their major pain points to grow our airport marketshare? What new airport product features can we introduce to grow rider demand? Are we able to forecast rider demand and use this prediction to adjust ride offerings or improve the rider experience? How can we optimize ride offerings for each rider to maximize conversion? Responsibilities Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Desi

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. As a Data Scientist working on Causal Inference in SCC, you'll partner with a strong team of engineers, product managers, designers, and operations leaders to deliver a personalized and exceptional experience for Lyft customers, using rigorous causal inference to guide the highest-stakes decisions we make. We're looking for a motivated and talented Data Scientist with deep causal inference expertise to join the SCC Data Science team. You'll partner closely with the area's tech lead on high-impact work spanning AI-powered support products, differentiated service, and operations optimization. The ideal candidate brings sharp applied inference intuition, a bias toward impact, and the ability to cut through ambiguity in complex problem spaces. You'll work on projects like: Design rigorous experiments and quasi-experiments to measure the causal impact of SCC product and AI-agent launches, and drive data-informed launch decisions. Build causal ML models to optimize concession budget allocation, targeting the right support credit, to the right rider or driver, at the right moment to maximize trust and business impact. Quantify the long-term effects of support-experience changes on rider and driver retention, and uncover heterogeneous treatment effects across our community. Deliver strategic insights on quality–cost tradeoffs, empowering leadership to balance service quality, coverage,

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As a Data Scientist on the Mapping team, you will collaborate with our world class team of scientists, engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our geospatial, behavioural and mobility data, and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers. Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. The Mapping team serves models and systems that determine the most efficient routes, fastest travel estimates and process real-time map data signals to detect traffic, closures and slowdowns. Working with our business and analytics partners, the team owns tools to ensure Lyft offers routes that our users trust. This will involve identifying and scoping opportunities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in Mapping, including: How do we accurately predict acute and chronic traffic conditions? How do we improve the recommendations of our routing algorithms? How do we keep our travel estimation promises to our riders and drivers? How do we benchmark and measure the success of our services? Responsibilities: Own the complete lifecycle of algorithmic solutions from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration Prioritize and lead deep dives into our data to uncover new product and business opportunities Partner closely with E

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. As a Data Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. Responsibilities: Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft Evolve data model and data schema based on business and engineering needs Implement systems tracking data quality and consistency Develop tools supporting self-service data pipeline management (ETL) SQL and MapReduce job tuning to improve data processing performance Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions Experience: Bachelor's degree in Compute

Our Purpose Mastercard powers economies and empowers people in 200&#43; countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Lead Data Scientist Overview: Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution. The Cyber and Intelligence Solutions team is responsible for innovation, development and management of our products and services to address evolving risk and security needs for all of Mastercard’s customers across the world including Banks, Merchants, Fintechs and of course consumers. The Lead Data Scientist will be a key contributor in helping Mastercard develop and deliver actionable insights and products to help issuers, acquirers and merchants reduce fraud. What will you do? -You will be a key player in helping Mastercard extract value from existing data sources in order to better understand, detect and prevent fraud. -Use your data science expertise and skills to analyze worldwide fraud data to gain insights regarding fraud. -Apply modeling techniques to identify and understand fraud to protect the MasterCard payment network. -Build and manage new fraud related products and services that will provide value to our customers and increase revenue. All about you: <br

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. As a Senior Software Engineer, Data on the Mapping team, you will collaborate with our world-class team of engineers, product managers, and scientists to grow and improve the quality of recommended routes and accuracy of our travel time estimations. You will lead the architecture and long-term technical direction of our offline experimentation tooling and route simulation services — the systems that let Lyft test routing changes safely before they reach production. You'll also build scalable data pipelines for experimentation, analytics, and machine learning models, along with the data governance and observability systems that keep them trustworthy. Your work will enable integration with partner teams and allow stakeholders across Engineering, Data Science, and Product to make data-informed decisions that directly impact Lyft’s growth and profitability. Our technology stack is based on the latest technologies such as AWS, Databricks, Kubernetes and Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers. Responsibilities Own core data pipelines end-to-end, building deep subject matter expertise in the systems you manage and defining/managing SLAs for pipelines, services, and datasets to ensure reliability at scale Serve as the technical owner and architectural lead for our offline experimentation platform and route simulation services, setting technical direction, evaluating trade-offs, and ensuring the systems scale with Lyft's routing and mapping ambitions Continuously evolve data models and schemas to meet business and engineering requirements Develop AI tools that support self-service management of data pipelines (ETL) and schema evolution, and perform han