16 Causal Inference Jobs

As a Quantitative Analyst at Google, your role will be crucial in driving data-informed decision-making across the organization. With a Master's degree in Statistics or Economics, or a related field, along with 8 years of experience in using analytics to tackle product or business challenges, you will be expected to leverage your expertise in coding (e.g., Python, R, SQL) and statistical analysis. Alternatively, if you hold a PhD, 6 years of relevant work experience will also be considered. Your responsibilities will revolve around conducting statistical data analysis encompassing linear models, multivariate analysis, causal inference, and sampling methods. Proficiency in statistical software such as SQL, R, Python, MATLAB, and pandas, as well as database languages, will be essential in executing tasks related to Statistical Analysis, Modeling, and Inference. Preferred qualifications for this role include the ability to translate analysis outcomes into actionable business recommendations. You should possess a deep understanding of causal inference methods like split-testing, instrumental variables, difference-in-difference methods, among others. Moreover, your experience should include selecting appropriate tools for resolving data analysis challenges, articulating business queries, and utilizing data-driven approaches to arrive at solutions. Familiarity with structural econometric methods will be an added advantage. In this position, you will collaborate with various teams and leaders within Google, partnering with Engineers and Product Managers to identify opportunities for design enhancements and assess improvements in advertising measurement products. Your role will involve defining questions related to advertising effectiveness, incrementality assessment, privacy impact, user behavior, brand building, bidding strategies, among others. You will be responsible for developing and implementing quantitative methods to address these questions, working with large and intricate data sets. Your analytical prowess will be put to the test as you tackle complex and non-routine analysis problems, applying advanced methods to derive meaningful insights. From data gathering and exploratory data analysis to model development and result delivery, you will play a vital role in shaping Google's operational efficiency and client solutions. By building and iterating on analysis pipelines, you will provide scalable insights and advocate for necessary changes in Google's data structures and metrics to drive product development forward.,

You are a motivated and technically skilled Data Scientist with 4+ years of experience in applying AI/ML techniques to solve real-world problems. You possess a solid foundation in machine learning, statistical modeling, and data analysis, with hands-on experience working with large datasets and deploying models in production environments. Your key responsibilities include designing, developing, and deploying machine learning models and AI solutions for business problems across multiple domains. You will collaborate with cross-functional teams including engineering, product, and analytics to identify opportunities for data-driven solutions. Conducting exploratory data analysis (EDA), feature engineering, and model selection using industry best practices are essential. You will also perform experiments, model validation, and performance tuning, as well as build reusable code and libraries for future use while contributing to data science platform improvements. Presenting findings and insights clearly to both technical and non-technical stakeholders is a crucial part of your role. You should have 4+ years of relevant experience in data science, with hands-on experience in machine learning, deep learning, or AI systems. Proficiency in Python and relevant libraries such as Pandas, Scikit-learn, TensorFlow, PyTorch, NumPy, etc., is required. A strong understanding of supervised, unsupervised, and reinforcement learning techniques is necessary. Experience with SQL, data wrangling, and working with large datasets is expected, and exposure to cloud platforms like AWS, Azure, or GCP is a plus. Familiarity with MLOps, model deployment, and version control (e.g., Git) is beneficial. Preferred qualifications include experience working with NLP, computer vision, or time-series forecasting, as well as familiarity with data visualization tools such as Matplotlib, Seaborn, Power BI, Tableau. An understanding of A/B testing, causal inference, and statistical hypothesis testing is advantageous. You should be able to work in a fast-paced, agile environment with minimal supervision and have experience in GenAI frameworks (OpenAI, Vertex AI), multi-agent architectures, and MLOps tooling. In terms of the tech stack, you should be familiar with languages and frameworks like Python, Java, SQL, JavaScript/TypeScript, and tools such as TensorFlow, PyTorch, and Scikit-learn. Cloud platforms like GCP Vertex AI, BigQuery, Cloud Functions, Cloud Run, Dataflow, and Pub/Sub are essential. Knowledge of data and MLOps tools like BigQuery, AlloyDB, MongoDB, Redis, relation databases (e.g., Oracle, MySQL, MSSQL), and MLOps tools (e.g., MLflow, Kubeflow, Airflow, Docker, Kubernetes) is required. Understanding of GenAI and agents such as Vertex AI Gemini, OpenAI, Claude, LangChain, LlamaIndex, FAISS, Pinecone, RAG pipelines, autonomous agents, multi-agent orchestration, memory modules, tool use, and prompt chaining is beneficial. Dev tools like GitHub Copilot, ChatGPT, Cursor AI, or any other Gen AI tools are also part of the tech stack you will work with.,

You are an exceptional and highly motivated Lead Data Scientist with experience in Data Science, Computer Science, Applied Mathematics, Statistics, or a closely related quantitative field. You will spearhead the design, development, and deployment of an automotive OEMs next-generation Intelligent Forecast Application. This pivotal role will leverage cutting-edge machine learning, deep learning, and statistical modeling techniques to build a robust, scalable, and accurate forecasting system crucial for strategic decision-making across the automotive value chain, including demand planning, production scheduling, inventory optimization, predictive maintenance, and new product introduction. As a recognized expert in advanced forecasting methodologies, you will possess a strong foundation in data engineering and MLOps principles. You will demonstrate a proven ability to translate complex research into tangible, production-ready applications within a dynamic industrial environment. This role demands not only deep technical expertise but also a visionary approach to leveraging data and AI to drive significant business impact for a leading automotive OEM. **Role & Responsibilities:** **Strategic Leadership & Application Design:** Lead the end-to-end design and architecture of the Intelligent Forecast Application, defining its capabilities, modularity, and integration points with existing enterprise systems. Develop a strategic roadmap for forecasting capabilities, identifying opportunities for innovation and the adoption of emerging AI/ML techniques. Translate complex business requirements and automotive industry challenges into well-defined data science problems and technical specifications. **Advanced Model Development & Research:** Design, develop, and validate highly accurate and robust forecasting models using a variety of advanced techniques including Time Series Analysis, Machine Learning, Deep Learning, Probabilistic Forecasting, and Hierarchical & Grouped Forecasting. Incorporate diverse data sources and conduct extensive exploratory data analysis to identify patterns and key features influencing automotive forecasts. Stay abreast of the latest academic research and industry advancements in forecasting, machine learning, and AI. **Application Development & Deployment (MLOps):** Architect and implement scalable data pipelines for ingestion, cleaning, transformation, and feature engineering of large, complex automotive datasets. Develop robust code for model training, inference, and deployment within a production environment. Implement MLOps best practices for model versioning, monitoring, retraining, and performance management. Collaborate closely with cross-functional teams to ensure seamless integration, deployment, and maintenance of the application. **Performance Evaluation & Optimization:** Define and implement rigorous evaluation metrics for forecasting accuracy and business impact. Perform A/B testing and comparative analyses to continuously improve forecasting performance. Identify and mitigate sources of bias and uncertainty in forecasting models. **Collaboration & Mentorship:** Work cross-functionally with various business units to understand their forecasting needs and integrate solutions. Communicate complex technical concepts and model insights clearly to technical and non-technical stakeholders. Provide technical leadership and mentorship to junior data scientists and engineers. **Requirements:** **Qualifications & Skills:** Education in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, or a closely related field. 5+ years of hands-on experience in a Data Scientist or Machine Learning Engineer role. Technical proficiency in Python, R, Machine Learning/Deep Learning Frameworks, Forecasting Specific Libraries, Data Warehousing & Big Data Technologies, Cloud Platforms, MLOps, Data Visualization, and strong analytical skills. **Preferred Qualifications:** Publications in top-tier conferences or journals, experience with real-time forecasting systems, familiarity with automotive data types, experience with distributed version control systems, and knowledge of agile development methodologies. **Soft Skills:** Exceptional communication, collaboration, intellectual curiosity, strategic thinking, mentorship, resilience, and adaptability. This role offers an unparalleled opportunity to make a significant impact on the strategic direction and operational efficiency of a global automotive leader, contributing directly to the future of intelligent manufacturing and supply chain management. If you are looking to play a pivotal role in shaping a rapidly growing venture studio, thrive in a collaborative, innovative environment, access professional development opportunities, and enjoy competitive benefits, then you may be a great fit for this position.,

As a Staff Data Scientist at Uber Eats, you will play a crucial role in enhancing the search experience for millions of users worldwide. Your deep statistical expertise will drive decision-making, improve product performance, and ensure that our evaluations and insights are based on methodological rigor. Your responsibilities will include conducting robust statistical analyses on complex datasets to identify product opportunities, shape roadmap priorities, and optimize user experiences in search. You will design and evaluate A/B tests and quasi-experiments, applying best practices in experimental methodology to ensure high-quality, unbiased insights. Building and maintaining statistical frameworks for defining and measuring ground truth will be a key aspect of your role, to identify reliable signals for evaluating search relevance, personalization, and user satisfaction. You will apply advanced sampling strategies to construct representative datasets for both offline and online evaluation pipelines, ensuring scalability and statistical power. Developing rigorous evaluation metrics that reflect real-world product performance and align closely with user and business goals will be essential. Additionally, you will lead initiatives to enhance causal inference practices across the team, applying methods like matching, regression discontinuity, and difference-in-differences where appropriate. Collaborating with product managers, engineers, and other scientists, you will translate open-ended product questions into structured analytical approaches. Providing mentorship and technical leadership to other scientists, you will promote a culture of statistical excellence and continuous learning within the team. To excel in this role, you should have an M.S. or Bachelor's degree in Statistics, Economics, Mathematics, Operations Research, Computer Science, or a related quantitative field. With 10+ years of industry experience in data science or applied analytics, ideally in consumer products, search, or recommendation systems, you should possess deep expertise in ground truth design and evaluation methodologies for complex user-facing systems. Your proven experience with statistical sampling techniques, offline evaluation pipelines, experimentation design, causal inference, and observational data analysis will be valuable. Proficiency in tools like SQL, Python, and R for data manipulation, modeling, and visualization is required. Excellent communication skills are essential, as you will need to present statistical findings clearly and influence product and engineering decisions through data. Having a strong product sense and the ability to balance analytical rigor with practical business impact will be advantageous in this role.,

You will join Salesforce, a company that aims to inspire the future of business through the integration of AI, data, and CRM. Upholding core values, Salesforce empowers companies across various industries to innovate and engage with customers in unique ways. As a member of the team, you will have the opportunity to become a Trailblazer, enhancing your performance, advancing your career, and contributing to positive change in the world. As an experienced Data Scientist, your primary responsibility will be to develop marketing attribution, causal inference, and uplift models to enhance the efficiency and effectiveness of marketing initiatives. This role will involve designing experiments and ensuring a consistent approach to experimentation and campaign measurement across marketing, customer engagement, and digital use cases. The ideal candidate will possess extensive experience in creating statistical models and AI/ML algorithms for marketing and digital optimization on large-scale datasets within a cloud environment. Rigorous testing and evaluation of algorithm performance will be essential, both during development and in production. Moreover, a deep understanding of statistical and machine learning techniques is necessary, along with a commitment to the ethical use of data in algorithm design. Key Responsibilities: - Develop statistical and machine learning models to enhance marketing effectiveness, including attribution models, causal inference models, and uplift models. - Create optimization and simulation algorithms to optimize marketing spend across channels and improve ROI. - Lead the entire model development lifecycle from ideation to deployment, monitoring, and tuning. - Design experiments to support marketing, customer experience, and digital campaigns, and collaborate with peers to establish consistent experimentation and measurement approaches. - Cultivate strong cross-functional relationships and collaborate with key partners throughout the organization. - Stay updated on innovations in enterprise SaaS, AdTech, paid media, data science, customer data, and analytics fields. Required Skills: - 8+ years of experience in designing models for marketing optimization using statistical and machine learning techniques. - Proficiency in developing advanced statistical techniques for experiment design and causal inference methods. - Expertise in programming languages such as Python, R, PySpark, Java, and SQL. - Experience with cloud platforms like GCP and AWS for model development and deployment is preferred. - Strong quantitative reasoning skills and the ability to provide data-driven business insights. - Excellent written and verbal communication skills with a collaborative mindset. - Ability to simplify complex problems and a creative approach to finding solutions. - B2B customer data experience and knowledge of Salesforce products are advantageous.,

At Instawork, our mission is to create meaningful economic opportunities for local businesses and skilled hourly professionals in communities around the world. We're building the leading AI-powered labor marketplace and we're looking for exceptional talent to help us scale quickly and make an even greater impact. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we're transforming the way the world works. As a Manager of Product Analytics, you will lead a team of product analysts embedded with cross-functional product teams. You'll play a central role in shaping how we measure success, identify opportunities for growth, and drive better decision-making through data. This role is ideal for a player-coach who thrives in fast-paced environments, understands marketplace dynamics, and is excited to help shape the trajectory of a product that has a real-world impact on our professionals and partners. What You'll Do: - Partner closely with Product, Engineering, and Design to shape product roadmaps and influence strategy with data. - Define and refine KPIs that accurately reflect product and business performance. - Develop insights that improve marketplace health; drive user activation and reduce churn; and optimize user engagement. - Lead and mentor a team of product analysts, creating a culture of curiosity, rigor, and business impact. - Establish best practices for analytics workflows, knowledge sharing, and stakeholder engagement. - Present findings and recommendations to stakeholders, including senior leadership, in a clear and concise manner. - Stay up-to-date with the latest industry trends and advancements in data analysis techniques. What We're Looking For: - 7+ years of experience in product analytics, data science, business operations or related roles, with at least 2 years managing analysts or data teams. - Track record of fostering talent in high-growth environments. - Strong proficiency in SQL and experience with experimentation and causal inference techniques. - Hands-on experience using BI tools like Mode, Tableau, or Looker, and scripting languages like Python or R. - Demonstrated success driving impact in a product-led or marketplace business. - Ability to synthesize complex analyses into clear, strategic recommendations for both technical and non-technical audiences. - Experience working in cross-functional teams with product managers, designers, and engineers. - Entrepreneurial self-starter that thrives in a fast-moving environment and is capable of independently seeking information, marshaling resources, and delivering results without waiting for direction. Instawork Values: - Bias for Action -- We are a growing team and an evolving product. We want a team of doers to drive the company forward, even if it means making decisions with incomplete information or being wrong. - Act Like an Owner -- Treat this company as though it is your own. Execute on the fundamentals, and act creatively to drive growth. Your ability to drive impact in any part of our company is only limited by your courage and conviction, not your job title. - Always Be Learning -- We are changing an entire industry. We strive to learn from each other and get better each day, week, and month, so that our team's learnings can compound and we can all improve, together. - Empathy, Trust, Candor -- Empathy for our business partners and professionals means we put ourselves in their shoes. Empathy for our colleagues means we are always upfront and honest with each other, which comes from trust. About Instawork: Founded in 2015, Instawork is the leading flexible work app for local, hourly professionals. Its digital marketplace connects thousands of businesses and more than five million workers, filling a critical role in local economies. Instawork has been featured on CBS News, the Wall Street Journal, The Washington Post, Associated Press, and more. In 2022, Instawork was ranked among the country's top 10% of fastest-growing companies by Inc. 5000 and was included in the Forbes Next Billion Dollar Startup list. Instawork was also named the 2022 ACE Award recipient for Best Innovation and one of the Best Business Apps by Business Insider. Instawork helps businesses in the food & beverage, hospitality, and warehouse/logistics industries fill temporary and permanent job opportunities in more than 25 markets across the U.S. and Canada. At Instawork, we constantly evaluate how to build an optimal work environment for success. Currently, we operate on a hybrid model, but we remain open to adapting our policies to meet the needs of our evolving business and team dynamics. As we continue to grow, we're seeking candidates who are excited about contributing to our in-person culture and open to the idea of working in-office up to 5 days a week. We value diversity on our team and firmly believe Instawork is stronger when we hire people who make their own unique contributions to our culture. We welcome all applicants and encourage candidates from underrepresented backgrounds to apply. To learn more about our company values, please visit: https://info.instawork.com/about Personnel Privacy Policy,

The Data Science team at Meesho plays a crucial role in devising creative solutions and building intelligent systems for millions of users across a wide range of product categories. As a Principal Data Scientist in the AdTech team, you will lead innovation in the advertising platform by leveraging advanced machine learning and statistical methods. Your responsibilities will include developing algorithms to optimize ad spend and ROI, designing frameworks to measure ad effectiveness, collaborating with cross-functional teams to implement AI/ML solutions, and providing strategic insights to tech and business leadership. Key Responsibilities: - Design and develop sophisticated algorithms for bidding and budget optimization. - Create frameworks for measuring ad effectiveness and ROI. - Collaborate with product and engineering teams to implement AI/ML solutions. - Communicate insights and recommendations to tech and business leadership. - Mentor junior data scientists and provide technical guidance. - Lead research initiatives in machine learning, auction theory, and advertising technology. Requirements: - B.Tech in Computer Science, Machine Learning, or a related field with a minimum of 6 years of experience in AI/ML research. - Proficiency in PyTorch or TensorFlow, and expertise in Python and big data technologies. - Experience in auction theory, predictive modeling, causal inference, and reinforcement learning. - Strong communication skills to convey complex concepts to technical and non-technical audiences. - Prior experience in mentoring junior data scientists and managing multiple problem statements. Preferred Qualifications: - M.Tech or Ph.D. in Computer Science with a specialization in Machine Learning. - 3+ years of experience applying machine learning in AdTech or related domains. - Exposure to real-time bidding systems, programmatic advertising, or ad exchanges. - Track record of successful research-to-product transitions. - Strong publication record in top AI conferences (e.g., NeurIPS, ICML, ICLR, KDD, CVPR, AAAI).,

The Conversational AI team at Walmart is responsible for building and deploying core AI assistant experiences across Walmart, catering to millions of active users globally. As a Staff Data Scientist, you will play a crucial role in leading the evolution of the AI assistant platform by developing highly scalable Generative AI systems and infrastructure. This hands-on leadership position requires expertise in machine learning, ASR, large-scale distributed systems, multi-modal LLMs, and more. Your responsibilities will include partnering with key business stakeholders to drive the development and planning of proof of concepts and production AI solutions within the Conversational AI space. You will be involved in translating business requirements into strategies, initiatives, and projects aligned with business objectives. Designing, testing, and deploying cutting-edge AI solutions at scale to enhance customer experiences will be a key aspect of your role. Collaboration with applied scientists, ML engineers, software engineers, and product managers will be essential in developing the next generation of AI assistant experiences. Staying updated on industry trends in Generative AI, Speech/Video processing, and AI assistant architecture patterns will be crucial. Additionally, providing technical leadership, guidance, and mentorship to a skilled team of data scientists, as well as driving innovation through problem-solving cycles and research publication, are integral parts of this role. To qualify for this position, you should have a Master's degree with 8+ years or a Ph.D. with 6+ years of relevant experience in Computer Science, Statistics, Mathematics, or a related field. A strong track record in a data science tech lead role, extensive experience in designing and deploying AI products, and expertise in machine learning, NLP, speech processing, image processing, and deep learning models are required. Proficiency in industry tools and technologies, a deep interest in generative AI, and exceptional decision-making skills will be assets in this role. Furthermore, you should possess a thorough understanding of distributed technologies, public cloud platforms, and big data systems, along with experience working with geographically distributed teams. Business acumen, research acumen with publications in top-tier AI conferences, and strong programming skills in Python and Java are also essential qualifications for this position. Join the Conversational AI team at Walmart Global Tech, where you will have the opportunity to make a significant impact, innovate at scale, and shape the future of retail while working in a collaborative and inclusive environment.,

You will be responsible for developing and implementing predictive models and machine learning algorithms to address logistics-related challenges like demand forecasting, route optimization, inventory prediction, and shipment delay analysis. This involves analyzing large volumes of structured and unstructured logistics data from systems like TMS (Transportation Management Systems), WMS (Warehouse Management Systems), and ERP platforms. Your role will also include designing and maintaining dashboards and visualizations to monitor supply chain KPIs, operational performance, and model outputs using tools such as Power BI, Tableau, or similar platforms. Collaboration with logistics, operations, procurement, and IT teams will be essential to comprehend business challenges and translate them into data science solutions. You will utilize SQL, Python, R, and big data tools to extract, clean, and prepare datasets for analysis and modeling purposes. Additionally, deploying models into production and monitoring their performance to ensure accuracy and reliability over time will be part of your responsibilities. In this position, you will contribute to strategic initiatives like logistics network design, warehouse automation, and sustainability optimization. Conducting A/B testing and causal inference to evaluate changes in supply chain processes and logistics strategies will also be a key aspect of your role. This is a full-time position with benefits including health insurance and provident fund. The work schedule is during day shifts and the work location is in person.,

You will be an Applied Economist - Full-Stack Data Science (R + Shiny) Intern at a fast-growing health-tech & wellness startup located in Noida. As part of the role, you will manage the complete data cycle, including extraction, cleaning, analysis, and visualization, to transform complex financial data into actionable insights. Your primary responsibilities will involve working with raw financial and operational data to extract, clean, analyze, and visualize information. You will be expected to create and maintain interactive dashboards using tools like Shiny, automate financial reporting, develop forecasting models, and collaborate with various teams to deliver data-driven insights. To excel in this role, you must have proficiency in R (preferred) or Python for handling real-world data, building Shiny dashboards for real-time insights, and possess strong analytical and problem-solving skills. A good understanding of financial metrics, forecasting, and the ability to communicate insights clearly are essential for success. The ideal candidate will have a background in Economics, Applied Statistics, or Data Science, with fluency in R, especially for dashboarding using Shiny. Additionally, you should have a strong grasp of causal inference, forecasting, and behavioral trends, along with experience in backend deployment for server-side operations. If you are looking for an opportunity to own and lead data-driven projects in a collaborative and learning-focused environment, where your work directly impacts company decisions, then this internship could be the perfect fit for you. Upon demonstrating exceptional performance during the 23-month internship, there is a high likelihood of a full-time job offer.,

As a key member of the GSK organization, you will be responsible for enhancing our disease understanding and shaping the future of the Asia Development Biostatistics function. Your role will involve utilizing statistical methods and machine learning techniques to support business critical projects and drive disease-aligned decision-making in R&D. By applying advanced statistical methodologies and collaborating with global functional groups, you will play a crucial role in optimizing analytical methods and ensuring robust evidence for informed decision-making. Your responsibilities will include identifying opportunities to enhance disease understanding, leading strategic projects within Asia Development Biostatistics, and presenting statistical principles and results to stakeholders at all levels. Additionally, you will interact with external scientific groups and vendors to contribute to innovation and the adoption of novel statistical methodologies within GSK Asia and the pharmaceutical industry. To be successful in this role, you should have a PhD in Statistics or a related field, along with a minimum of 10 years of experience in drug development and 5 years of experience in a leadership role. Your knowledge of the drug development process and demonstrated ability to influence positive change will be essential. Additionally, experience in applying various statistical methodologies, digital fluency, and strong communication skills will be beneficial for this position. If you are a proactive and driven individual with a passion for patients, a keen interest in clinical statistics, and a track record of delivering high-quality results under tight deadlines, we encourage you to apply. This role offers the opportunity to lead innovation in Asia Development Biostatistics and contribute to the success of GSK on a global scale.,

As a Data Scientist at Objectways located in Chennai, you will have the opportunity to be part of a team that is driving AI innovation and solving real-world problems by leveraging cutting-edge machine learning and reasoning technologies. Our projects are ambitious and diverse, ranging from agent trajectory prediction to complex reasoning systems, multimodal intelligence, and preference-based learning. We are looking for a talented individual like you who is eager to explore the boundaries of applied AI. In this role, you will be responsible for designing and developing machine learning models for both structured and unstructured data. You will work on agent trajectory prediction, complex reasoning, preference ranking, and reinforcement learning. Additionally, you will handle multimodal datasets and develop reasoning pipelines across text, image, and audio modalities. Your responsibilities will also include validating and optimizing prompts for large language model performance and translating research into scalable, production-level implementations. Collaboration with cross-functional teams such as Engineering, Product, and Research is essential to ensure the success of our projects. To qualify for this position, you should have a minimum of 4 years of hands-on experience in Data Science or Machine Learning roles. Proficiency in Python, PyTorch/TensorFlow, scikit-learn, and ML lifecycle tools is required. You should also demonstrate expertise in at least one of the following areas: trajectory modeling, preference ranking, or multimodal systems. Experience with LLM prompt engineering, complex reasoning algorithms, graph-based methods, and causal inference is highly beneficial. Strong problem-solving, analytical thinking, and communication skills are essential for success in this role. Preferred skills for this position include familiarity with tools like LangChain, Hugging Face, or OpenAI APIs, exposure to RLHF (Reinforcement Learning from Human Feedback) or prompt-tuning, and experience with deploying ML models in production environments using technologies such as Docker and MLflow. By joining Objectways, you will have the opportunity to work on high-impact, next-generation AI challenges, collaborate with top talent from various domains, and enjoy a competitive salary with benefits and a learning budget.,

As the Associate Director - Analytics at Games24x7, you will play a crucial role in leading the analytics function for our flagship fantasy sports product, My11Circle. Your responsibilities will include developing and executing the data strategy, building and mentoring a high-performing analytics team, and driving data-informed decisions across all aspects of the My11Circle product lifecycle. You will be responsible for defining key performance indicators (KPIs) and establishing robust reporting frameworks to track product performance and user behavior. Collaborating with various stakeholders, such as product management, engineering, and marketing teams, you will provide actionable insights based on data analysis to drive product innovation, user growth, and revenue optimization. To excel in this role, you should possess a strong analytical background, deep understanding of product analytics principles, and proven experience in leading analytics teams. Your strategic thinking, combined with a hands-on approach, will enable you to translate complex data into actionable insights that directly impact the success of My11Circle. Your leadership skills will be crucial in building, mentoring, and leading a talented team of data analysts and scientists dedicated to supporting the My11Circle product. By fostering a data-driven culture within the team and organization, you will create an environment that promotes professional development and continuous learning. Additionally, you will oversee the design, development, and execution of in-depth analysis on user acquisition, engagement, retention, monetization, and gameplay patterns within My11Circle. Utilizing various analytical techniques, you will uncover key insights and trends, develop dashboards and reports, and drive the adoption of self-service analytics capabilities within the team. Furthermore, you will collaborate with the product team to design and analyze A/B tests and experiments to optimize product features, user flows, and marketing campaigns. You will also work with data engineering teams to ensure data availability, accuracy, and reliability for My11Circle analytics and contribute to the development of a scalable data infrastructure. If you are a passionate and experienced analytics leader with a deep understanding of product analytics and a desire to make a significant impact on a leading fantasy sports platform, we encourage you to apply. Join us at Games24x7, where you can leverage your expertise and drive data-informed decisions to shape the future of online gaming and fantasy sports.,

Role - Lead AI Engineer Experience: 3+ years in AI/ML Location: Gurgaon, work from office About Tap Health: Tap Health is a deep-tech platform that is transforming chronic care management with AI and changing how you access health information. Powered by our proprietary Medical AI model, VaiD, Tap Health is designed to make healthcare accessible to millions. We are developing next-generation Digital Therapeutic products that redefine chronic illness management through AI-driven, hyper-personalized care. Our platform helps users manage conditions such as diabetes, hypertension, PCOS, pregnancy and asthma by delivering daily structured digital therapeutics, lifestyle interventions, personalized nutrition and exercise guidance and real-time monitoring, all without requiring human intervention. Leveraging AI and adaptive algorithms, Tap Health dynamically personalizes each users care journey, delivering enhanced insights, interventions, motivation, adherence and clinical outcomes at a fraction of traditional healthcare costs. Beyond Digital Therapeutics, the Tap Health platform also provides free primary illness diagnosis based on symptoms and instant health advice through a seamless, voice-first experience. www.tap.health Role Overview: Lead AI Engineer We are hiring a full-time Lead AI Engineer in Gurgaon to drive AI-driven healthcare innovations. The ideal candidate has 3+ years of AI/ML experience, 6+ months of GenAI production experience, and 1+ year of hands-on GenAI product development. You need to have a strong data science background and have expertise in GenAI, Agentic AI deployments, causal inference, and Bayesian modeling, with a strong foundation in LLMs and traditional models. You will be collaborating with the AI, Engineering, and Product teams to build scalable, consumer-focused healthcare solutions. As a Lead AI Engineer, you will be the go-to expertthe engineer others turn to when they hit roadblocks. You will mentor, collaborate, and enable high product velocity while fostering a culture of continuous learning and innovation. Skills & Experience The ideal candidate should have the following qualities: Strong understanding of fine-tuning, optimization, and neural architectures. Hands-on experience with Python, PyTorch, and FastAI frameworks. Experience running production workloads on one or more hyperscalers (AWS, GCP, Azure, Oracle, DigitalOcean, etc.). In-depth knowledge of LLMshow they work and their limitations. Ability to assess the advantages of fine-tuning, including dataset selection strategies. Understanding of Agentic AI frameworks, MCPs (Multi-Component Prompting), ACP (Adaptive Control Policies), and autonomous workflows. Familiarity with evaluation metrics for fine-tuned models and industry-specific public benchmarking standards in the healthcare domain. Knowledge of advanced statistical models, reinforcement learning, and Bayesian inference methods. Experience in Causal Inference and Experimentation Science to improve product and marketing outcomes. Proficiency in querying and analyzing diverse datasets from multiple sources to build custom ML and optimization models. Comfortable with code reviews and standard coding practices using Python, Git, Cursor, and CodeRabbit.,

Job Requirements Education: Bachelors degree (Statistics, Business Analytics, Data Science, Math, Economics, etc.) Masters degree preferred (MBA/MS/M.Tech in Computer Science or related field) Experience: 5–7 years in a Data Science/Advanced Analytics role Behavioral Skills: Delivery Excellence Business Orientation Social Intelligence Innovation and Agility Knowledge & Technical Skills: Functional analytics experience (Supply Chain, Marketing, Customer Analytics, etc.) Statistical modeling using tools such as R, Python, KNIME Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference) Experience building and evaluating machine learning models MLOps tools and practices (MLflow, DVC, Docker, etc.) Strong Python programming (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.) Experience with big data technologies (AWS, Azure, GCP, Hadoop, Spark) Familiarity with relational (MySQL, SQL Server) and non-relational (MongoDB, DynamoDB) databases BI and reporting tools (Power BI, Tableau, Alteryx) Proficiency with Microsoft Office applications (especially Excel) Roles & Responsibilities Analytics & Strategy: Analyze large-scale structured and unstructured data to develop insights and machine learning models across various business domains Apply statistical and machine learning techniques to generate value from operational, financial, and customer data Recommend best-fit algorithms and models with clear justifications for business use Leverage cloud platforms for modeling and big data analysis; utilize data visualization tools to communicate results Operational Excellence: Follow industry-standard coding practices and development lifecycles Formulate hypotheses, develop analytics frameworks, and bring structure to complex problems Collaborate with Data Engineering to maintain core data infrastructure and automate analytical processes Stakeholder Engagement: Work cross-functionally with business stakeholders, engineers, and visualization experts to deliver impactful projects Communicate complex models and results to non-technical stakeholders in a clear and compelling way

Job Description Company Overview Lifesight is a fast-growing SaaS company focused on helping marketers leverage their own data & advanced AI to improve marketing decision making. Our mission is to make it easy for non-technical marketers to navigate the privacy-first era with a modern and unified marketing measurement platform that is designed to drive incremental impact, optimize spend and achieve their business goals. We have a team of 130 serving 300+ customers across 5 offices in the US, Singapore, India, Australia, and the UK. We are a profitable company and our product is being adopted rapidly globally and we need the best people onboard the team to accelerate our growth. Position Overview We are looking for a seasoned professional with deep experience in the marketing measurement industry to join and lead our marketing science team. The marketing science team at Lifesight sits in the intersection of customer success, sales and marketing. In this role, you will be responsible for managing our marketing science team and its initiatives. You will be responsible for driving revenue by closing deals and ensuring that our customers' needs are met. You will also be responsible for evangelizing our platform in the market through online and offline activities in order to drive demand and build trust. You will get the unique opportunity to work on growing a trending AI-powered measurement platform, in a massive industry and get to truly drive its adoption & success. What Youll Do Manage a team of marketing scientists who assist in solving our customer measurement needs using Marketing Mix Modeling, universal attribution, incrementality testing and causal inference. Evangelize our UMM platform, articulating its value proposition to a diverse range of brands across multiple industries. Own and achieve a revenue target for the US market driven through strategic initiatives that you set up. Study and understand the customers business goals and KPIs to offer expert recommendations and actionable insights to achieve them using our platform. Manage the portfolio of customer accounts, communications and engagement with the support of our team of customer success and support executives, to ensure customer satisfaction. Craft compelling thought leadership content for social media and other channels to engage potential clients and industry leaders. Oversee custom consulting and professional services work for customers who require them. Contribute to our product roadmap and feature development alongside our product, data science and engineering team. Identify and stay ahead of industry trends, track competitor movements and find differentiators to continuously improve our offering and solutions. Work closely with global sales and marketing to ensure alignment and cohesiveness in go-to-market strategies. Train and coach new marketing scientists and other team members to enable career growth and skill development. Requirements You are perfect for the role if you: Bachelors degree or above in Business Management, BI/Analytics, Economics, Statistics, Mathematics and/or Marketing 6+ years experience with strong foundation in data science and/or marketing science, with significant experience in business analytics, marketing analytics, attribution modeling, marketing mix modeling, experimentation projects. Highly accomplished analytical professional with strong problem solving skills and great attention to detail. Proven track record of working with mid-market and enterprise brands across industries. Proven track record of managing teams and delivering results for customers. Excellent project management and account management capabilities, with exceptional customer communication and servicing skills Exceptional ability to communicate complex data science concepts in simple terms. Skilled in developing strategies that drive revenue and market share. Experienced in leveraging social media platforms for brand promotion and thought leadership. Ability to collaborate effectively with diverse global teams. Benefits Whats in it for you? As a team, we are concerned with not only the growth of the company but each others personal growth and well-being too. Along with our desire to utilize smart technology and innovative engineering strategies to make peoples lives easier, our team also bonds over our shared love for all kinds of tea, movies & fun-filled Friday events with a prioritizing healthy work-life balance. 1. Working for one of the fastest-growing and successful MarTech companies in times 2. Opportunity to be part of an early member of the core team to build a product from scratch starting from making tech stack choices, driving and influencing the way to simplify building complex products. 3. Enjoy working in small teams and a non-bureaucratic environment 4. Enjoy an environment that provides high levels of empowerment and space to achieve your objectives and growth with the organization. 6. Work in a highly profitable and growing organization, with opportunities to accelerate and shape your career. 7. Great benefits - apart from competitive compensation & benefits