15 Regression Modeling Jobs

Salary : 20 to 35 LPA Exp: 3 to 8 years Location :/Gurugram/Bangalore/Pune Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

At Allstate, great things happen when our people work together to protect families and their belongings from life's uncertainties. For over 90 years, our innovative drive has kept us a step ahead of our customers" evolving needs. From advocating for safety measures like seat belts and airbags to being a leader in pricing sophistication, telematics, and device and identity protection. This role is responsible for leading the use of data to make decisions. You will develop and execute new machine learning predictive modeling algorithms, code tools using machine learning/predictive modeling for business decisions, integrate new data to improve modeling results, and find solutions to business problems through machine learning/predictive modeling. In addition, you will manage projects of small to medium complexity. We are seeking a Data Scientist to apply machine learning and advanced analytics to solve complex business problems. The ideal candidate will possess technical expertise, business acumen, and a passion for solving high-impact problems. Your responsibilities will include developing machine learning models, integrating new data sources, and delivering solutions that enhance decision-making. You will collaborate with cross-functional teams to translate insights into action, from design to deployment. Key Responsibilities: - Design, build, and validate statistical and machine learning models for key business problems. - Perform data exploration and analysis to uncover insights and improve model performance. - Communicate findings to stakeholders, collaborate with teams to ensure solutions are adopted. - Stay updated on modeling techniques, tools, and technologies, integrating innovative approaches. - Lead data science initiatives from planning to delivery, ensuring measurable business impact. - Provide mentorship to junior team members and lead technical teams as required. Must-Have Skills: - 4 to 8 years of experience in applied data science, delivering business value through machine learning. - Proficiency in Python with experience in libraries like scikit-learn, pandas, NumPy, and TensorFlow or PyTorch. - Strong foundation in statistical analysis, regression modeling, classification techniques, and more. - Hands-on experience with building and deploying machine learning models in cloud environments. - Ability to translate complex business problems into structured data science problems. - Strong communication, stakeholder management, analytical, and problem-solving skills. - Proactive in identifying opportunities for data-driven decision-making. - Experience in Agile or Scrum-based project environments. Preferred Skills: - Experience with Large Language Models (LLMs) and transformer architectures. - Experience with production-grade ML platforms and orchestration tools for scaling models. Primary Skills: Business Case Analyses, Data Analytics, Predictive Analytics, Predictive Modeling, Waterfall Project Management. Shift Time: Shift B (India). Recruiter Info: Annapurna Jha, email: ajhat@allstate.com. About Allstate: The Allstate Corporation is a leading insurance provider in the US, with operations in multiple countries, including India. Allstate India is a strategic business services arm focusing on technology, innovation, and operational excellence. Learn more about Allstate India here.,

Role & responsibilities Primarily works at the Product/Program Level Provide input for budget planning Manage and Deliver assignments with quality and within timelines Possible to have direct reports; Possible to oversee contingent workers and/or vendors; likely to provide training to others; Analyzes needs to manage resources Responsible for statistical aspect of study designs and data analyses for clinical studies Provides study design input and consultation for clinical endpoint assessments and sample size planning Prepares, or oversees the preparation of statistical sections of clinical protocols in collaboration with key stakeholders, as deemed necessary Writes, or oversees the writing of, statistical analysis plans Conducts, or oversees the conduct of, analyses to support clinical study reports, abstracts, manuscripts, and other documents to support the marketing of Teva products Leads the conduct of analyses and document preparation to support global regulatory submissions, including briefing packages, integrated analyses, and regulatory responses. Collaborates with outsourcing partners and oversees conduct of statistical aspects of outsourced studies, as appropriate Proactively assesses and identifies processes that require improvement Participates in department initiatives to further the effectiveness of global statistics Implements innovative and cutting-edge clinical trial design, methodology and analysis Preferred candidate profile Ph.D./MS in Statistics/Biostatistics (or related field)

Requirement : Bachelor's Degree in Computer Science, Operations Research, Statistics, or related field. Knowledge of R, or Python Knowledge of building regression and classification models Familiarity with any or all of, Regularization methods: Lasso, Ridge Ensemble methods: Random Forest, Boosting Time Series analysis: Auto-regression, moving average, etc. Graphs modeling Support Vector Machines Decision trees Preferred : Master's or higher degrees. Industry experience in the field of Data Science. Participation in competitions like Kaggle, Netflix Data Challenge. Open source contributions in areas of Data Science (Machine Learning, Deep Learning, Statistical Learning). Worked on Scala and/or Spark. Understanding of generative AI concepts, such as transformers, diffusion models, and LLMs

We are looking for a Data Scientist to help us gain useful insight out of raw data. Data Scientist responsibilities include working with the data science team, planning projects and building analytics models. You should have a strong problem-solving ability and a knack for statistical analysis. If youre also able to align our data products with our business goals, wed like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data. Key Responsibilities Responsible for overseeing the data scientists team and data specialists Teach, lead, and counsel colleagues on new techniques or solutions Collaborate with data and software engineers to enable deployment of sciences and technologies that will scale across the companys ecosystem Responsible for the conception, planning, and prioritizing of data projects Responsible for building analytic systems and predictive models as well as experimenting with new models and techniques Ensure that data projects align with organizational goals Minimum Qualification Master's degree in Computer Science, Operations Research, Econometrics, Statistics or related technical field 3+ years of experience solving analytical problems using quantitative approaches Experience communicating quantitative analysis results Knowledge with relational databases and SQL Development experience in any scripting language (PHP, Python, Perl, etc.) Knowledge of statistics (e.g., hypothesis testing, regressions) Experience manipulating data sets through statistical software (ex. R, SAS) or other methods Technical Skills - Must have Programming – Python (Preferred) / R ML Models – i. Regression – Linear, Logistic, Multinomial, Mixed effect Classification – Bagging & Boosting (Random Forest), Decision tree, SVM Clustering – K-Means, hierarchical, DB-Scan Time series – ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCM Neural Networks (Deep learning), Naive Bayes Excel and SQL Dimensionality Reduction – PCA, SVD etc. Optimization Techniques – Linear programming, Gradient Descent, Genetic Algorithm Cloud – Understanding of Azure / AWS offerings, Setting up ML pipeline of cloud Good to have – Visualization – Tableau / Power BI / Looker / QlikView Data management – HDFS, Spark, Advanced Excel Agile Tools – Azure DevOps, JIRA Pyspark Big Data/Hive Database IDE: Pycharm

Job Summary: We are looking for a highly skilled Data Scientist with deep expertise in time series forecasting, particularly in demand forecasting and customer lifecycle analytics (CLV). The ideal candidate will be proficient in Python or PySpark, have hands-on experience with tools like Prophet and ARIMA, and be comfortable working in Databricks environments. Familiarity with classic ML models and optimization techniques is a plus. Key Responsibilities • Develop, deploy, and maintain time series forecasting models (Prophet, ARIMA, etc.) for demand forecasting and customer behavior modeling. • Design and implement Customer Lifetime Value (CLV) models to drive customer retention and engagement strategies. • Process and analyze large datasets using PySpark or Python (Pandas). • Partner with cross-functional teams to identify business needs and translate them into data science solutions. • Leverage classic ML techniques (classification, regression) and boosting algorithms (e.g., XGBoost, LightGBM) to support broader analytics use cases. • Use Databricks for collaborative development, data pipelines, and model orchestration. • Apply optimization techniques where relevant to improve forecast accuracy and business decision-making. • Present actionable insights and communicate model results effectively to technical and non-technical stakeholders. Required Qualifications • Strong experience in Time Series Forecasting, with hands-on knowledge of Prophet, ARIMA, or equivalent Mandatory. • Proven track record in Demand Forecasting Highly Preferred. • Experience in modeling Customer Lifecycle Value (CLV) or similar customer analytics use cases – Highly Preferred. • Proficiency in Python (Pandas) or PySpark – Mandatory. • Experience with Databricks – Mandatory. • Solid foundation in statistics, predictive modeling, and machine learning Locations: Mumbai/Pune/Noida/Bangalore/Jaipur/Hyderabad

Job Description Summary Sandoz continues to go through an exciting and transformative period as a global leader and pioneering provider of sustainable Biosimilar and Generic medicines. As we continue down this new and ambitious path, unique opportunities will present themselves, both professionally and personally. Join us, the future is ours to shape! Job Purpose: The Group Head, Forecasting will lead the forecasting team, developing accurate and insightful forecasts, and providing strategic guidance to support business decisions across therapy areas for in-line and pipeline products. In addition to ensuring a high-quality forecasts the role requires driving synergies across units and regions, exploring avenues for innovation and implementing solutions that bring speed and scalability. This role requires a deep understanding of forecasting methodologies, strong analytical skills, and the ability to collaborate effectively with cross-functional teams. Job DescriptionJob Description Your Key Responsibilities: Your responsibilities include, but not limited to: Lead the forecasting team and provide guidance to develop and maintain accurate short-term and long-term forecasts for various business units. Expected span of control of 20+ associates Critically evaluate the current forecasting processes and methodologies and explore areas of innovation and improvement in standardization, speed and accuracy Ensure Sandoz forecasting approaches are best-in-class leveraging AI and next gen forecasting tools and methodologies Lead the team to utilize advanced statistical and analytical techniques to analyse historical data and identify trends Collaborate with cross-functional teams on enterprise level forecasting initiatives as well as to gather relevant data and insights Provide strategic guidance and recommendations based on forecast data to support business planning and decision-making. Prepare and present detailed forecast reports to senior management and stakeholders, communicating complex data and insights in a clear and concise manner. Stay updated with industry trends and best practices in forecasting and data analysis. Skills and Competencies: In-depth knowledge of the industry, including market dynamics, competitive landscape, and regulatory environment. Experience in leveraging advanced statistical and analytics techniques (expertise in AI/ML will be added advantage) Strong team management and project management skills, especially with critical and time-sensitive deliverables Ability to manage multiple projects and senior stakeholders simultaneously, and effectively prioritize to meet critical deadlines Ability to align forecasting activities with the organizations strategic goals and provide actionable insights. Excellent communication, leadership and organizational skills What youll bring to the role: Minimum Requirements: Educational Background: Advanced degree in areas such as Management/Statistics/Decision Sciences/Engineering/Life Sciences and related fields Languages: Fluent in English (written and spoken) Good communication, presentation, and interpersonal skills Experience: 12+ years of relevant experience in pharma forecasting in a leading pharma or consulting organisation (experience in generic pharma industry will be a plus) You'll receive: Breakdown of benefits received in this role. Include flexible working, learning and development opportunities as well. Why Sandoz? Generic and Biosimilar medicines are the backbone of the global medicines industry. Sandoz, a leader in this sector, touched the lives of almost 500 million patients last year and while we are proud of this achievement, we have an ambition to do more! With investments in new development capabilities, state-of-the-art production sites, new acquisitions, and partnerships, we have the opportunity to shape the future of Sandoz and help more patients gain access to low-cost, high-quality medicines, sustainably. Our momentum and entrepreneurial spirit is powered by an open, collaborative culture driven by our talented and ambitious colleagues, who, in return for applying their skills experience an agile and collegiate environment with impactful, flexible-hybrid careers, where diversity is welcomed and where personal growth is encouraged! The future is ours to shape! #Sandoz

Role Overview: We are looking for an experienced Data Scientist specializing in Market Mix Modeling (MMM) to join our team. The candidate will be responsible for developing predictive models to measure marketing effectiveness, optimize budget allocation, and derive actionable insights from large datasets. This role requires expertise in statistical modeling, machine learning, and data visualization to support data-driven decision-making for our premium FMCG Client. Roles & Responsibilities: 1.Develop and implement Market Mix Models (MMM) to evaluate the impact of marketing activities on sales and brand performance. 2.Analyze large-scale marketing, sales, and consumer data from multiple sources to uncover trends and insights. 3.Apply statistical techniques (e.g., regression modeling, time-series analysis, Bayesian modeling) to measure ROI across marketing channels. 4.Work with cross-functional teams to optimize media spend and marketing investments. 5.Use Python, R, SQL, and SAS for data extraction, cleaning, and modeling. 6.Build automated reporting dashboards using Power BI, Tableau, or Excel to visualize model outputs. 7.Conduct scenario analysis and simulations to forecast business outcomes. 8.Communicate technical findings to non-technical stakeholders, ensuring data-driven decision-making. 9.Continuously improve models by incorporating machine learning algorithms and external factors (macroeconomic, seasonal, competitive). 10.Collaborate with business teams to translate insights into actionable marketing strategies. Desired Candidate Skills: Bachelors/Masters degree in Statistics, Data Science, Economics, Mathematics, or a related field. 4-7 years of hands-on experience in Market Mix Modeling (MMM), econometrics, or marketing analytics. Strong expertise in statistical analysis, regression modeling, and causal inference techniques. Proficiency in Python, R, SQL, SAS, and experience with ML libraries (Scikit-learn, TensorFlow, XGBoost). Hands-on experience with BI tools (Power BI, Tableau, Looker) for data visualization. Prior experience in FMCG, Retail, or Consumer Goods industry is highly preferred. Strong business acumen and ability to translate data into actionable insights. Excellent stakeholder management and communication skills. Join us in leveraging data-driven strategies to optimize marketing effectiveness and drive business growth.

Job Responsibilities- Create and validate analytical datasets using on real-world data sources (e.g., claims data, electronic health records) based on study protocols and inclusion/exclusion criteria. Conduct descriptive and inferential statistical analyses (e.g., hypothesis testing, regression modelling, survival analysis) Develop and validate statistical algorithms for advanced data analyses (e.g., propensity score matching, machine learning) Contribute to the development of study protocols, statistical analysis plans, abstracts/posters, manuscripts, and study reports. Collaborate with cross-functional teams (e.g., epidemiologists, clinicians, biostatisticians) to design and execute RWE studies.

Experience - 3-15 yrs (Across different levels) Designation - Senior Engineer/Module Leader/Technical Leader Skill - Artificial Intelligence, Machine Learning, Deep Learning, NLP, LLM Location - Chennai, Kochi and Bangalore Leading a team of data scientists with roadmap and vision. Planning data projects. Building analytic systems and predictive models. Managing a team of data scientists, and machine learning engineers. Involve in pre-sales and building proposals. Apply strong expertise in machine-learning, deep learning, NLP, data mining, and information retrieval to design, prototype, and build the next-generation analytics engines and services Responsibilities : Lead data mining and collection procedures Ensure data quality and integrity Interpret and analyze data problems Conceive, plan and prioritize data projects Build analytic systems and predictive models Test performance of data-driven products Visualize data and create reports Align data projects with organizational goal Understands business problems and designs end-to-end analytics use cases Develops complex models and algorithms that drive innovation throughout the organization. This may include improving on-time performance, network planning, etc., Conducts advanced statistical analysis to provide actionable insights, identify trends, and measure performance Collaborates with model developers to implement and deploy scalable solutions Provides thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders Qualification & Other Attributes: 3-15 years experience in a statistical and/or data science role Proven experience as a Data Scientist or similar role Strong organizational and leadership skills Degree in Computer Science, Data Science, Mathematics, or similar field Deep knowledge and experience in Large Language Models (LLM), Strong knowledge on Generative AI Deep knowledge of machine learning, statistics, optimization or related field Experience in Linear and non-Linear Regression models including Multiple and Multivariate Experience in Classification models including Ensemble techniques Experience in Unsupervised models including K-Means, DBSCAN, LOF Rich Experience in NLP techniques Experience in Deep Learning techniques like CNN, RNN, GAN, Markov etc (Any 3 or 4) Strong real-time experience with atleast one of the machine language softwares like R, Python, Matlab is mandatory. Good knowledge in Explainable AI Experience working with large data sets, simulation/ optimization and distributed computing tools (Map/Reduce, Hadoop, Hive, Spark, etc.) Excellent written and verbal communication skills along with strong desire to work in cross functional teams Attitude to thrive in a fun, fast-paced start-up like environment Additional advantage of having experience in semi, unstructured databases like MongoDB, Cassandra, ArangoDB, Couchbase, GraphDB, etc Optional: programming in C, C++, Java, .Net Interested candidates can share their updated resume at megha.chattopadhyay@aspiresys.com

We're Hiring: Data Scientist Databricks & ML Deployment Expert Location: Mumbai Experience: 3-7 Years Apply Now! Are you passionate about deploying real-world machine learning solutions? We're looking for a versatile Data Scientist with deep expertise in Demand forecasting, Azure, Databricks, PySpark , Deployment , Classical ML and end-to-end ML deployment to drive impactful projects in the Retail and Automotive domains. What You will Do Develop scalable ML models (Regression, Classification, Clustering) Deliver advanced use cases like CLV modeling , Predictive Maintenance , and Time Series Forecasting Design and automate ML workflows on Databricks using PySpark Build and deploy APIs to serve ML models (Flask, FastAPI, Django) Own model deployment and monitoring in production environments Work closely with Data Engineering and DevOps teams for CI/CD integration Optimize pipelines and model performance (code & infrastructure level) Must-Have Skills Strong hands-on with Databricks and PySpark Proven track record in ML model development & deployment (min. 2 production deployments) Solid grasp of Regression, Classification, Clustering & Time Series Proficiency in SQL , workflow automation, and ELT/ETL processes API development (Flask, FastAPI, Django) CI/CD, deployment automation, and ML pipeline optimization Familiarity with Medallion Architecture Domain Expertise Retail: CLV, Pricing, Demand Forecasting Automotive : Predictive Maintenance, Time Series Nice to Have MLflow, Docker, Kubernetes Cloud: Azure, AWS, or GCP If you're excited to build production-ready ML systems that create real business impact, we want to hear from you! Apply Now to chaity.mukherjee@celebaltech.com or DM us for more info.

Responsibilities: * Deliver engaging training sessions on data science principles using Python, R, Excel & SQL. * Design & develop AI/ML curriculum for corporate clients.

Salary : 20 to 35 LPA Exp: 3 to 8 years Location :/Gurugram/Bangalore/Pune Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

v Construct , a Pune based Construction Technology company seeks a Senior Data Scientist for their Data Science and Analytics team which is a tight-knit group of Data Scientists and AI Engineers along with Data Analysists and Data Engineers that support all data aspects of DPR business. This team drives up with passion of Transforming this Construction Industry by the use of cutting edge technology enabled with strong AI/ ML Solutions. Location: Pune: Magarpatta or Baner Glimpse of Projects: Creation of GPT for Construction Industry on Construction Data (Unstructured & Structured Data). Use Computer Vision to help Object Detection on 2D Drawings and 3D BIM Models Detailed use of Stats frameworks for Predicting Losses on Construction Site Data or to predict win/ loss of opportunities with clients. Predict Quantities required for similar type of sites etc. Automation AI has deep integration with other groups of Construction Operations to automate our current work processes and make them more efficient using pre-built Models, Azure ML Services or other ML Techniques. Key Responsibilities: Think strategically & collaborate with cross-functional teams to identify business use cases and solutionize with scalable technical solutions. Analyze construction project data and develop predictive models using traditional data science methods and Generative AI. Apply machine learning algorithms to improve key processes such as project execution, safety, and risk assessment. Design, Lead & Own scalable end-to-end development of predictive, ML models, from hypothesis generation to deployment and monitoring. Build, validate, and optimize machine learning and statistical models using best-in-class techniques. & QC models developed by Jr. Data Scientists and ML Engg. Work closely with Engineering & business team to understand the data, business terms, processes to create, suggest and implement solutions accordingly. Stay current with advancements in data science and machine learning to help leveraging Companys data. Use statistical techniques to detect anomalies and optimize operational workflows, ensuring projects are delivered on time and within budget Collaborate with product managers and business leaders to drive the implementation of data-driven decisions. Plus to have ability of visualizing insights using BI tools. Qualification: Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, or a related -field. 8-10 years of professional experience with atleast 6 years of experience in data science, machine learning, and analytics, with a proven track recordof delivering impactful data-driven solutions. Experience working in dynamic, fast-paced environments, with the ability to manage multiple projects simultaneously as well as should be able to do production or work on project personally as required. Proven Experience, Strong business acumen and ability to translate technical insights into actionable business strategies & communicate to stakeholders in business language. Experience working with construction-related data or similar industries (e.g., engineering, manufacturing) is a plus. Technical Skills: Expertise in programming languages such as Python, R, or Scala. Proficiency in machine learning, AI & Statistics frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). Strong experience in predictive analytics, clustering, classification, regression & multi-variate techniques. Hands-on experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib). Familiarity with cloud platforms (AWS, Azure preferably), knowledge about Azure ML Services & Snowflake would be plus one Strong understanding of SQL and working with relational databases. Good to have knowledge of NLP(Natural Language Processing) and Computer Vision. About vConstruct : vConstruct specializes in providing high quality Building Information Modeling and Construction Technology services geared towards construction projects. vConstruct is a wholly owned subsidiary of DPR Construction. vConstruct has 100+ team members working on Software Development, Data Analytics, Data Engineering and AI/ML. We have matured Data Science practice and growing at accelerated pace. For more information, please visit www.vconstruct.com About DPR Construction: DPR Construction is a national commercial general contractor and construction manager specializing in technically challenging and sustainable projects for the advanced technology, biopharmaceutical, corporate office, and higher education and healthcare markets. With the purpose of building great things, great teams, great buildings, great relationshipsDPR is a truly great company. For more information, please visit www.dpr.com

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether its medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity . We are seeking an exceptional Principal Data Scientist with 15+ years of experience to lead technical innovation in Shipments ETA prediction across multiple transportation modes. This senior individual contributor role requires deep expertise in predictive modeling, supply chain analytics, and transportation logistics, with particular strength in regression problems and modern deep learning architectures. You will be the technical authority driving ETA accuracy improvements for Full Truck Load (FTL), Less-than-Truckload (LTL), Parcel, and complex multi-pickup/delivery scenarios. What you'll be doing Technical Leadership & Innovation ETA Modeling Excellence : Design and implement state-of-the-art predictive models for shipment ETAs across FTL, LTL, Parcel, and multi-stop delivery scenarios Cross-Modal Optimization : Develop unified frameworks that account for mode-specific characteristics while maintaining consistency across transportation types Complex Routing Intelligence : Build sophisticated models for multi-pickup and delivery scenarios with dynamic routing optimization Real-time Prediction Systems : Architect scalable solutions that provide accurate ETAs with sub-second latency for millions of shipments Advanced Analytics & Research Time Series Mastery : Lead development of advanced time series models incorporating seasonality, weather, traffic, and operational constraints Geospatial Analytics : Implement cutting-edge location-based models combining GPS tracking, route optimization, and historical patterns Feature Engineering Innovation : Create novel features from telematics data, driver behavior, carrier performance, and external data sources Uncertainty Quantification : Develop probabilistic models that provide confidence intervals and risk assessments for ETA predictions Strategic Technical Influence Architecture Design : Define the technical roadmap for ETA prediction systems, balancing accuracy, scalability, and operational efficiency Cross-Functional Collaboration : Partner with Product, Engineering, and Operations teams to translate business requirements into technical solutions Industry Leadership : Represent the company at conferences, publish research, and establish thought leadership in transportation analytics Mentorship & Knowledge Transfer : Guide junior data scientists and establish best practices for transportation modeling Who You are Education & Experience Master's degree in Data Science, Statistics, Computer Science, Mathematics, Operations Research, Industrial Engineering, or related quantitative field (required) 15+ years of data science experience with at least 5 years in transportation, logistics, or supply chain analytics Deep ETA/Transportation Knowledge : Proven track record of building production ETA systems for multiple transportation modes Supply Chain Expertise : Understanding of logistics operations, carrier networks, and transportation economics Scalable Systems Experience : Experience with high-volume, real-time prediction systems serving millions of requests Technical Excellence Core Data Science Mastery Expert-level EDA skills : Advanced proficiency in transportation data analysis, anomaly detection, and pattern recognition Advanced Regression Modeling : Deep expertise in time series regression, spatial regression, and hierarchical modeling Deep Learning Expertise : Hands-on experience with sequence models, attention mechanisms, and transformer architectures for temporal prediction Statistical Modeling : Mastery of Bayesian methods, survival analysis, and probabilistic forecasting Specialized Transportation Skills Geospatial Analytics : Proficiency with PostGIS, spatial indexing, routing algorithms, and map-matching techniques Time Series Forecasting : Advanced knowledge of ARIMA, state-space models, neural forecasting (LSTM, GRU, Transformers) Optimization Methods : Experience with route optimization, network flow problems, and multi-objective optimization Real-time Systems : Understanding of streaming data processing, model serving, and low-latency prediction systems Technical Infrastructure Programming Mastery : Expert-level Python/R with pandas, numpy, scikit-learn, TensorFlow/PyTorch, and transportation-specific libraries Big Data Platforms : Experience with Spark, Kafka, and distributed computing for large-scale transportation data Database Systems : Advanced SQL skills with time-series databases (InfluxDB, TimescaleDB) and spatial databases Cloud & MLOps : Proficiency with cloud platforms (AWS, GCP, Azure), containerization, and ML deployment pipelines Preferred Qualifications Advanced Degree : PhD in Data Science, Statistics, Computer Science, Mathematics, Operations Research, Industrial Engineering, Transportation Engineering, or related quantitative field Domain Certifications : Professional certifications in supply chain, logistics, or transportation (APICS, CSCMP, SOLE, etc.) Industry Recognition : Publications in transportation/logistics conferences (INFORMS, TRB) or top-tier ML venues Leadership Experience : Track record of leading technical initiatives and influencing product strategy Open Source Contributions : Contributions to transportation analytics or forecasting libraries Transportation Domain Challenges You'll Solve Multi-Modal ETA Complexity FTL Challenges : Long-haul routing with driver hours-of-service, fuel stops, and carrier-specific performance patterns LTL Complexity : Hub-and-spoke networks with consolidation delays, sorting times, and terminal-specific processing Parcel Dynamics : Last-mile delivery optimization with address-level precision and delivery attempt modeling Multi-Stop Scenarios : Complex pickup/delivery sequences with dynamic routing and time window constraints Advanced Technical Problems Data Fusion : Integrating GPS tracking, weather data, traffic patterns, carrier performance, and operational constraints Uncertainty Modeling : Providing confidence intervals and risk assessments for critical shipments Real-time Adaptation : Updating predictions as new information becomes available during transit Performance Optimization : Balancing model complexity with sub-second prediction requirements What You can expect from the role Technical Excellence : Access to cutting-edge infrastructure, datasets, and research resources Industry Impact : Opportunity to shape the future of transportation analytics and supply chain optimization Professional Growth : Conference speaking opportunities, research publication support, and industry networking Innovation Environment : Collaborative culture with world-class engineering and product teams