Data Science Manager Jobs

About Sigmoid: Sigmoid empowers enterprises to make smarter, data-driven decisions by blending advanced data engineering with AI consulting. We collaborate with some of the world’s leading data-rich organizations across sectors such as CPG-retail, BFSI, life sciences, manufacturing, and more to solve complex business challenges. Our global team specializes in cloud data modernization, predictive analytics, generative AI, and DataOps, supported by 10+ delivery centers and innovation hubs, including a major global presence in Bengaluru and operations across the USA, Canada, UK, Netherlands, Poland, Singapore, and India. Recognized as a leader in the data and analytics space, Sigmoid is backed by Peak XV Partners and has consistently received accolades for innovation and rapid growth. Highlights include being named a ‘Leader’ in ISG’s Specialty Analytics Services for Supply Chain (2024), a two-time ‘India Future Unicorn’ by Hurun India, and a four-time honoree on both the Inc. 500 and Deloitte Technology Fast 500 lists. The below role is for our Bengaluru office. Director – Data Science Why Join Sigmoid? Sigmoid provides the opportunity to push the boundaries of what is possible by seamlessly combining technical expertise and creativity to tackle intrinsically complex business problems and convert them into straight-forward data solutions. Despite being continuously challenged, you are not alone. You will be part of a fast-paced diverse environment as a member of a high-performing team that works together to energize and inspire each other by challenging the status quo Vibrant inclusive culture of mutual respect and fun through both work and play Roles and Responsibilities: Convert broad vision and concepts into a structured data science roadmap, and guide a team to successfully execute on it. Handling end-to-end client AI & analytics programs in a fluid environment. Your role will be a combination of han

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. Dun & Bradstreet Technology and Corporate Services India LLP is looking for candidates for the role of Senior Analyst to support the Data Science team. The candidate needs to work closely with the team based in India and across a range of Analytics leaders who are located globally to fulfill the deliverables on a timely basis

We are looking for a Data Scientist to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quantitative equity fund that manages over $78+ billion USD in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-oiled machine responsible for generating key investment insights that drive trades. Leveraging data analytics, finance knowledge and cutting-edge technology, we aim to ensure that new and useful data products are continuously ready for research. Do you love the idea of evaluating and integrating large proprietary data sources into valuable applications? Are you a wizard at transforming ‘messy reality’ into high quality data assets? As a core member of our team, you will collaborate with investment and data experts to tackle challenging problems, and to continuously expand our capabilities in the data space. Based on the west coast in Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment outcomes and overall success. What You Will Do This is an exciting full-time role for individuals who are enthusiastic about learning the quantitative equity investment management business and excited to tackle a broad range of investment, mathematical, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data science, machine learning, AI, and process engineering skillsets to accelerate the Quantitative Equity Team’s data preparation and modelling functions. Your specialized role will involve building, scaling, managing and evaluating our integrated data model, in direct support of alpha research. You will be supported with coaching and mentorsh

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. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

Work Experience Required: 8 - 12 Years Experience in programing (Python, R, SQL, NoSQL,Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction. Proven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights Drive excellent project management required to deliver complex projects, including effort/time estimation. Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy Define Technology/ Strategy and Roadmap for client accounts, and guides implementation of that strategy within projects Run regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders Manage the team-members, to ensure that the project plan is being adhered to over the course of the project Manage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates. Build a trusted advisor relationship with the IT management at clients and internal accounts leadership. Build

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices : New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role : You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning, we would like to talk to you. Role: ALDS Mandate Skills & Competencies: Experience in Programming (Python, R, SQL, NoSQL, Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as NumPy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and c

ROLE SUMMARY We are looking for a Senior Data Scientist to lead complex data science engagements that combine traditional statistical modelling with Generative AI. You will work hands-on with very large datasets across disparate systems and formats, translate ambiguous business problems into rigorous analytical solutions, and present those solutions clearly to C-level stakeholders. This is a delivery-first role with a fast track into technical leadership: alongside your own project work, you will help guide junior data scientists and shape how Lynx builds and ships data science solutions. KEY RESPONSIBILITIES Solution Design & Delivery Design and deliver end-to-end solutions for defined data science problems, combining classical modelling, data transformation, and Generative AI / LLM techniques. Work hands-on with very large datasets across disparate stores and formats, from ingestion and transformation through to modelling and validation. Apply statistical and machine learning methods to business problems such as customer retention, campaign management, and commercial performance optimisation. Client Communication & Leadership Present results and prepare client-ready materials for project stakeholders, including C-level audiences, translating technical work into clear business narratives. Lead smaller data science workstreams, with support from internal leadership and the PMO, including day-to-day guidance for junior team members. Partner with delivery and account teams to scope problems, set realistic timelines, and manage stakeholder expectations. Knowledge Building Create reusable documentation, presentations, and code libraries during projects so future engagements can build on prior work. Participate in internal education, research, and knowledge-sharing initiatives that raise the technical bar across the practice. SKILLS, QUALIFICATIONS AND EXPERIENCE 8+ years of overall experience in data science, with a track record of leading analytic

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices : New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role : You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning we would like to talk to you. Function : Data Science and Analysis → Data Science / Machine Learning Desired Skills & Competencies: Strong learning acumen Team Management High sense of ownership Ability to work in a fast-paced and deadline-driven environment Loves technology Highly skilled at Data Interpretation Problem solver Good exposure to machine learning concepts and algorithms Must be fluent with any one of Python, R, Java Strong in statistical & machine learning concepts Knowledge of Python Libraries - SciPy, NumPy, Pandas, I Python, Scikit-learn Knowledge of distributed big data processing (PySpark, Jupyter, Linux, AWS) Responsibilities: Hypothesis testing, insights generation, root cause analysis, factor analysis Statistical model (predictive & prescriptive) development using various statistical & machine learning techniques/algorithms Test/train the model, Improve Model accuracy, Monitor model performance Data Extraction from EDW/Big Data Platform, Dataset Preparation (creation of base data, aggregation

Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. Discord is looking for a seasoned technical leader to join our Data team as a Staff Data Engineer. You will drive technical vision and strategy for our analytical data infrastructure which facilitates the transformation and semantic layer that powers clean, tested, well-documented datasets that the company can trust and self-serve from. The data your team builds won't just inform internal decisions, it will underpin the metrics we share with investors, partners, and the public, requiring exceptional rigor, auditability, and precision. This role works closely with Data Governance, Data Science, Product, Finance, and Engineering teams. This role reports to the Director of Data Engineering. What You'll Be Doing Define technical strategy and architectural direction for analytics data infrastructure, building and maintaining enterprise-scale curated datasets and data models Own the design and implementation of data governance programs end to end, by partnering with stakeholders and translating policy requirements into flexible and configurable infrastructure in partnership with Data Platform Engineering. Design and build sophisticated data abstractions and analytical frameworks using SQL, Python, and modern data stack technologies Develop data quality frameworks, monitoring, anomaly detection, and alerting at massive scale, with governance, lineage tracking, and change management rigor appropriate for externally reported numbers Drive adoption of consistent data modeling patterns, naming conventions, documentation norms, and metric governance standards across the data organization Lead cross-functional

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our Fraud, Losses, and Financial Crime Data Science team builds the models and data products that protect Stripe and its users from fraud, account takeover, and financial crime. We own the full fraud and loss modeling stack - from account takeover detection and card fraud classification to merchant-level loss estimation, unsupervised anomaly detection, and financial crime risk modeling. We partner with Fraud Engineering, Financial Crimes Engineering, and Risk Operations to bring these systems into production and ensure they have measurable impact on Stripe's financial integrity and user trust. What you'll do We're looking for a Data Scientist to join the Fraud Data Science team. In this role, you'll build and improve the models that power Stripe's fraud detection and loss management systems. You'll work closely with Fraud Engineering and Risk Operations to move models from research to production, and you'll use data to surface insights that shape fraud strategy across the business. Data scientists on this team apply supervised and unsupervised machine learning, statistical mod

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. The Product Data Science team is looking for a Full-stack Senior Data Scientist to come aboard and be part of Snowflake’s most critical initiatives. In this role, you will work closely with our Product and Engineering teams on everything from core operations, to innovative AI/ML tools, to our fastest-growing new and experimental features. You will work on long-running analytical initiatives yielding substantial product enhancements. This is a strategic, high-impact role that will help shape the future of Snowflake products and services. PLEASE NOTE: The position level is determined during the interview process and is influenced by various factors, including experience, educational attainment, skill level requirements, and overall interview performance. AS A SENIOR FULL STACK DATA SCIENTIST AT SNOWFLAKE YOU WILL: Be a proactive partner to Product Management and Engineering to shape feature roadmaps and help design metrics and analytical workflows to evaluate their success and effectiveness. Build efficient data models and high quality production pipelines and partner with Engineering for all necessary telemetry. Build scalable and extensible analytics/ML/causal inference frameworks to uncover feature usage patterns, subtle issues with the system, potential performance enhanc

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be. Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business. About the Ads Data Science Team: The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling. About the Role: Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal

Opportunity Overview: As a Staff Data Scientist at Cohere Health, you will serve as a technical leader across high-priority initiatives, shaping how data science is applied to some of the most complex challenges in healthcare. You’ll drive the design of advanced analytical and modeling solutions, influence strategic direction, and partner deeply across Product, Clinical, and Engineering to deliver scalable, high-impact outcomes. This role goes beyond execution. You’ll define approaches, set standards, and guide others in solving ambiguous, high-leverage problems. You’ll play a critical role in advancing the maturity of data science at Cohere while contributing directly to improving clinical and operational decision-making. What you’ll do: Lead the design and execution of complex, high-impact data science initiatives across multiple domains Define analytical frameworks and modeling approaches for ambiguous, strategic problem spaces Partner with senior stakeholders to shape problem definition, prioritize opportunities, and influence decision-making Develop and deploy advanced models and scalable analytical solutions that drive measurable outcomes Establish best practices for experimentation, model development, and analytical rigor across the team Mentor and guide other data scientists, providing technical leadership and elevating team capabilities Drive cross-functional alignment to ensure solutions are practical, scalable, and integrated into workflows ISMS roles and responsibilities: Good knowledge of Information security Oversee specific business processes within the ISMS. Responsible to manage the ISMS documentation, conduct risk assessments, and implement risk treatment plans. Risk Owners are responsible for identifying, assessing, and managing risks within their areas of responsibility. They are also responsible for implementing risk treatment plans. Conduct the BCP and other test related to information security continuity along with CISO Responsible for monitor

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. We are accepting applications for this position until 10/16/2026 Position Overview: At Freddie Mac, you will have meaningful work to help build a better housing finance system and support homeownership and rental housing opportunities across the nation. Our internship and graduate programs provide opportunities to tackle complex challenges, contribute to strategic initiatives, and build valuable relationships with industry professionals. As a Quantitative Risk Management Intern within Enterprise Risk Management (ERM), you will apply advanced analytical, technical, and quantitative skills to support risk management activities at one of the nation's largest financial institutions. You will gain hands-on experience working on real-world projects, collaborating across teams, and leveraging emerging technologies – including artificial intelligence and automation—to enhance risk management practices and business outcomes. Our Impact: Enterprise Risk Management (ERM) helps build and maintain a strong, effective, and efficient risk management framework across Freddie Mac. We provide independent oversight and assessment of financial and non-financial risks while promoting a culture of accountability, innovation, and sound risk management. Our quantitative teams leverage advanced analytics, data science, modeling, automation, and emerging technologies to support enterprise-wide decision-making and risk oversight. As AI and automation continue to transform the financial services industry, our teams p

Data Scientist The Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value . Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling . We understand our company’s goals and proactively inform their direction with data so that our product can help more teams do great things. As a Data Scientist at Asana, you’ll help us ask the right questions and answer them rigorously. You’ll work closely with our Pro duct and Business teams to understand their goals and proactively inform their direction with data. You’ll keep taking on new responsibilities as you grow—from defining core metrics to building machine learning models and keeping the data flowin g in our pipelines This role is based in our Warsaw office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . We offer a Contract of Employment (UoP) for our employees in Poland . What you’ll achieve Design and analyze experiments to measure the impact of new product features. Investigate high-level questions like “What are the collaborative patterns of the most successful teams using Asana?” Add new metrics and aggregations to our data warehouse to make new classes of questions answerable. Build models to predict the growth trajectory of different customer segments. Partner with cross-functional stakeholders across engineering, product management, and business teams to drive data-informed decision-making. About you Bachelor's Degree in Computer Science, Math, Statistics, Engineering, a related quantitative field, or equivale