Senior Manager, Data Science - Marketing Analytics & Data Science

Your Experience at a Glance

We’re hiring a Data Scientist for our client delivers advanced data, analytics, and digital transformation solutions to help organizations modernize and drive business insights.

As a Data Scientist, you will play a key role in developing and deploying demand forecasting and pricing models, leveraging advanced statistical and machine learning techniques. You will collaborate closely with data engineers and business stakeholders to extract, transform, and analyze large datasets, ensuring robust and scalable solutions. This position requires strong ownership of model development, from data pipeline integration to model evaluation and reporting. Your work will directly impact business decision-making and operational efficiency, contributing to KPIP’s mission of enabling data-driven transformation.

KPIP is a global consulting and technology services firm specialising in data, analytics, and digital transformation. Serving a diverse range of industries, KPIP empowers organisations to modernize their data ecosystems and unlock actionable business insights. The company is recognized for its expertise in delivering scalable solutions, fostering a culture of innovation, and driving measurable impact for clients worldwide.

Key Responsibilities

● Develop and implement demand forecasting and pricing models using advanced statistical and machine learning techniques.

● Extract, transform, and analyze large datasets using Python and SQL to support model development and business insights.

● Collaborate with data engineers to build and maintain robust, scalable data pipelines for model training and inference.

● Apply regression, classification, time-series forecasting, ensemble methods, and feature engineering to solve business problems.

● Work with business stakeholders to understand requirements and translate them into actionable data science solutions.

● Create automated reports and dashboards to present and track model outputs and performance.

● Continuously evaluate and improve model accuracy and effectiveness based on business feedback and new data.

● Document methodologies, processes, and results to ensure transparency and reproducibility.

● Stay updated with the latest advancements in data science and machine learning to drive innovation within the team.

Required Skills

● Proven experience in demand forecasting and predictive modeling.

● Strong proficiency in Python, including pandas, NumPy, scikit-learn, and TensorFlow or PyTorch.

● Expertise in SQL for data extraction and transformation.

● Solid understanding of statistical and machine learning techniques such as regression, classification, time-series forecasting, ensemble methods, and feature engineering.

● Ability to analyze and interpret large, complex datasets to generate actionable insights.

● Experience collaborating with data engineers to develop scalable data pipelines.

● Strong problem-solving skills and attention to detail.

● Excellent communication skills for presenting technical concepts to non-technical stakeholders.

Nice to Have

● Experience with customer segmentation, recommendation systems, and sentiment analysis.

● Knowledge of inventory optimization, promotion uplift modeling, and campaign analysis.

● Familiarity with churn prediction models.

● Proficiency in Power BI for creating automated reports and dashboards.

● Experience in developing and maintaining data pipelines for model training and inference.

Why Join?

Join to work on impactful data science projects that drive real business outcomes and innovation. You’ll tackle complex technical challenges, collaborate with talented professionals, and have opportunities for continuous learning and growth, fosters a culture of collaboration, excellence, and data-driven decision-making, empowering you to make a meaningful difference in a dynamic environment.

About the Employment Model

Direct Hire (Client Payroll) : For this role, you’ll be hired directly by the client and be part of their internal team. Straatix supports the hiring process, but your employment, payroll, and benefits are all managed by the client.

Sr.Data Scientist,Python, AI ML

We are looking for a skilled Data Scientist to analyze complex datasets, develop predictive models, and generate actionable insights that support business decisions. The ideal candidate should have strong statistical, analytical, and programming skills, along with hands-on experience in machine learning.

We are seeking a Senior Data Science & ML Associate with 4+ years of applied ML experience to build and ship models end-to-end from data prep and feature engineering to training, evaluation, and deployment driving measurable business impact.

Key Responsibilities

• Build, train, and evaluate ML and deep-learning models

• Engineer features and prepare data at scale

• Deploy models and monitor production performance

• Partner with stakeholders to frame problems and metrics

• Communicate results and drive decisions

• Iterate on models from business feedback

Mandatory Skills

• 4+ years applied machine learning

• Strong Python (Pandas, NumPy, scikit-learn)

• Classical ML and deep learning (TensorFlow/PyTorch)

• Solid statistics and experiment design

• SQL and data wrangling at scale

• Model deployment / MLOps exposure

Nice to Have: NLP or computer vision; cloud ML (SageMaker, Azure ML)

🚀 We’re Hiring | Data Scientist 🧠📊

Ready to turn data into real-world intelligence? Join us and work on exciting AI/ML & data-driven solutions!

🔹 Experience: 8+ Years

🔹 Must-Have Skills:

🐍 Python | 🤖 Machine Learning | ☁️ Cloud | 🧠 NLP | 📊 Data Visualization

📍 Location: Pune

💼 Work Mode: Work from Office

If you're passionate about Data Science, AI & solving complex business problems, we’d love to hear from you!

📩 Interested? Kindly text

#Hiring #DataScientist #DataScience #MachineLearning #Python #NLP #AI #Cloud #DataVisualization #TechJobs #HiringNow

About Starbond

Starbond is a growing direct-to-consumer brand focused on delivering high-quality products and an excellent customer experience. We are looking for a hands-on Marketing Manager who can turn data, customer insights, and strong execution into profitable growth.

About the Role

The Marketing Manager will own Starbond’s direct-to-consumer growth engine across paid acquisition, retention, lifecycle marketing, content, SEO, answer engine optimization (AEO), social media, conversion optimization, and agency performance. This role requires a strong command of unit economics—including customer lifetime value (LTV), customer acquisition cost (CAC), CAC payback period, gross margin, and contribution margin—and the ability to convert these metrics into sound growth decisions.

You will directly manage marketing agencies across Meta, Google, email, and AEO while leading the internal Marketing team, setting clear performance standards, and giving the CEO timely visibility into results, risks, and recommended actions.

Key Responsibilities

DTC Growth and Customer Acquisition

• Develop and lead the DTC acquisition strategy across Meta Ads, Google Ads, Shopify, email, SEO, social media, Amazon alignment, and other relevant channels.
• Manage marketing for profitable growth—not revenue or ROAS alone—by incorporating product margin, contribution margin, retention, and customer quality into decisions.
• Establish acceptable CAC thresholds by product, customer segment, campaign, and channel, and recommend when to scale, restructure, reduce, or discontinue investment.
• Align advertising, creative, landing pages, offers, product positioning, inventory availability, and operational readiness.

LTV, Retention, and Lifecycle Marketing

• Maintain a clear and consistent LTV methodology using customer revenue, purchase frequency, retention, gross margin or contribution margin, and cohort data.
• Analyze LTV and retention by acquisition source, product, cohort, and customer segment, and use the findings to improve channel and offer decisions.
• Lead strategies that improve repeat purchase rate, purchase frequency, average order value, cross-sell, replenishment, retention, and win-back performance.
• Oversee email and lifecycle marketing quality, segmentation, deliverability, revenue contribution, and customer communication accuracy.

Paid Advertising and Conversion

• Oversee paid media strategy, budget pacing, campaign structure, audience strategy, creative testing, attribution, and landing-page performance.
• Establish clear testing, scaling, optimization, and stop-loss rules, and require decisions to be supported by sufficient data and financial context.
• Review performance at the channel, campaign, audience, creative, product, and cohort levels.
• Partner with the Web Developer on Shopify priorities, site performance, conversion rate optimization, tracking, and quality assurance.

Agency and Vendor Management

• Directly manage marketing agencies across Meta, Google, email, and AEO, including scopes of work, deliverables, timelines, communication standards, SLAs, KPIs, reporting, ownership, and escalation procedures.
• Use agency scorecards and recurring performance reviews to track KPI attainment, SLA compliance, output quality, timeliness, efficiency, and business results.
• Require root-cause analysis and time-bound corrective action plans for missed targets, SLA breaches, quality issues, reporting gaps, or inefficient spend.
• Independently validate agency recommendations and recommend contract expansion, renegotiation, reduction, replacement, or termination when appropriate.
• Ensure Starbond retains access to and ownership of advertising accounts, data, dashboards, creative files, documentation, and intellectual property.

Content, Creative, and Brand

• Maintain an active content and creative pipeline supported by clear briefs, owners, deadlines, QA standards, and success metrics.
• Ensure reliable content-production support is available when external resources are required.
• Create a structured process for testing creative concepts, hooks, formats, messages, offers, and calls to action.
• Protect product positioning and perceived value by avoiding excessive reliance on discounting and ensuring marketing claims are accurate and supportable.
• Ensure approved assets are properly named, organized, and stored in company-owned systems.

Team Leadership, Process, and Reporting

• Lead the internal Marketing team by setting clear responsibilities, deadlines, quality standards, KPIs, communication expectations, and individual performance targets.
• Conduct regular coaching, one-on-ones, performance reviews, and accountability conversations; identify skill gaps and coordinate development or corrective action with HR.
• Make timely recommendations regarding training, role clarity, workload changes, reassignment, or other performance actions when standards are not met.
• Create and maintain marketing processes, approval flows, reporting definitions, campaign documentation, and quality-control systems.
• Maintain a weekly marketing scorecard that distinguishes leading and lagging indicators and explains what changed, why it changed, and what action is required.
• Proactively escalate material risks and present concise, financially grounded recommendations to the CEO.

What Success Looks Like

• Marketing data, forecasts, campaign reports, creative briefs, and recommendations are accurate, validated, and financially grounded.
• Campaigns, agency deliverables, reports, corrective actions, and launches are completed on time, with blockers escalated early.CAC, LTV, LTV:CAC, MER, ROAS, contribution margin, retention, and cohort performance are consistently defined and used to guide decisions.
• Marketing investment produces profitable customer growth, stronger retention, faster learning, higher-quality execution, and stronger brand protection.
• The Marketing team and external agencies operate with clear ownership, measurable standards, and consistent accountability.

What We’re Looking For

• Proven experience leading DTC or e-commerce marketing across paid acquisition, retention, lifecycle marketing, content, and conversion optimization.
• Strong working knowledge of CAC, LTV, LTV:CAC, MER, ROAS, contribution margin, retention, cohort analysis, and marketing attribution.
• Experience managing Meta Ads, Google Ads, email marketing, SEO, AEO, Shopify, and agency partners.
• Demonstrated ability to manage budgets and make channel decisions based on profitability and customer quality.
• Experience leading and developing marketing team members, setting KPIs, and managing performance.
• Strong analytical judgment with the ability to challenge assumptions, validate agency recommendations, and translate data into clear actions.
• Excellent written and verbal communication, with a proactive and concise reporting style.
• Highly organized, accountable, and comfortable working in a remote, fast-moving environment.

Role Overview 

As a Data Scientist, you will work with business stakeholders, AI engineers, and domain experts to transform data into actionable insights and intelligent solutions. You will develop machine learning models, perform statistical analysis, and contribute to AI-driven products that create measurable business impact. 

Key Responsibilities 

Data Science & Machine Learning 

• Analyze structured and unstructured data to identify patterns, trends, and business opportunities.  
• Perform exploratory data analysis (EDA), feature engineering, and data preparation.  
• Develop, evaluate, and optimize machine learning models for prediction, classification, clustering, and forecasting.  
• Apply statistical techniques to solve business problems and validate model performance.  
• Design and execute experiments to improve model accuracy and business outcomes.  

 AI Solution Development 

• Collaborate with AI Engineers, Data Engineers, and domain experts to build AI-powered solutions.  
• Translate business requirements into scalable data science approaches.  
• Contribute to Generative AI and advanced analytics initiatives where applicable.  
• Document methodologies, model performance, and key findings.  

 Required Technical Skills 

• Strong programming skills in Python and SQL for data analysis, feature engineering, and machine learning.  
• Strong understanding of Statistics, Probability, Linear Algebra, and Calculus as applied to machine learning and data science.  
• Experience with Exploratory Data Analysis (EDA), data preprocessing, feature engineering, feature selection, and handling missing or imbalanced data.  
• Good understanding of Supervised, Unsupervised, and Ensemble Machine Learning algorithms, including their assumptions, strengths, limitations, and appropriate use cases.  
• Strong knowledge of Regression, Classification, Clustering, Time Series Forecasting, Dimensionality Reduction, Recommendation Systems, and Anomaly Detection techniques.  
• Experience with Model Evaluation, Cross-Validation, Hyperparameter Optimization, Bias-Variance Trade-off, Feature Importance, Explainable AI (XAI), and Performance Metrics.  
• Understanding of Statistical Inference, Hypothesis Testing, Probability Distributions, Sampling Techniques, Confidence Intervals, and A/B Testing.  
• Experience translating business problems into analytical approaches and developing scalable, data-driven solutions.  
• Working knowledge of Generative AI, Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG) is preferred. 

Preferred Qualifications 

• Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.  
• 2–4 years of experience developing machine learning or data science solutions.  
• Experience working on end-to-end data science projects in a business environment.  

 Nice to Have 

• Exposure to Generative AI, LLMs, RAG, or Agentic AI.  
• Experience with Computer Vision or Natural Language Processing (NLP).  
• Familiarity with cloud-based AI platforms.  
• Knowledge of construction, engineering, manufacturing, or industrial domains.  
• Participation in hackathons, research, Kaggle competitions, or open-source projects.  

 Soft Skills 

Strong analytical and problem-solving skills, effective communication and collaboration, ownership mindset, adaptability, continuous learning, and a passion for innovation.

CraftMyPlate is a Hyderabad-based platform for micro-events: house parties, birthdays, office celebrations, and small gatherings. One thing hasn't changed since day one. Every order comes from someone making a specific, personal decision: this occasion, this many people, this budget, this date. We win by understanding that decision better than anyone else does.

We are now investing in the systems (data, growth, and eventually AI-driven automation) that let us make that same quality of decision at scale, without needing to grow headcount just to keep up. That investment is partly backed by funding we recently brought in, but the funding is not the story. It simply means we can now hire someone senior enough to own this problem properly, instead of solving it in pieces.

If you join now, you are not joining a company that has already figured everything out and just needs someone to run the machine. You are joining at the point where the machine is still being designed. What you build in the next year will still be the foundation two years from now.

About the Role

We are hiring a Growth Lead to own two things at once: how many people know about us, and how much revenue that awareness turns into. Not one or the other. Both, as a single connected number.

Here is what makes this role different from most growth roles you have seen: the infrastructure is already built. Tracking, attribution, and engagement systems are already in place and working. Our content and performance teams already execute well within the current playbook. You are not being hired to set any of that up. You are being hired to direct it and extract return from it.

That means your job is judgment, not motion. You decide which channels get more budget and which get cut. You decide what message goes to which segment. You decide what "working" means, and you prove it with numbers, not activity. The team executes. You are accountable for the return.

We need someone who has done this before, at a company where marketing spend had to answer to revenue, not just to reach. Someone who can point to a previous role and say plainly: this is what we spent, this is what we made back, and this is what I specifically changed to move that number.

What "Good" Looks Like (Market Standard)

This is not a vague "be strategic" ask. In most growth-stage consumer companies, a Growth Lead's performance is judged against a small set of hard numbers. We expect the same here:

• Return on ad spend (ROAS) or marketing efficiency ratio (MER) improving quarter over quarter across paid channels, not just held flat
• CAC to LTV ratio healthy enough to support scaling spend, not just acquiring volume (a commonly cited industry bar is a ratio meaningfully above 1:3, CAC to LTV)
• CAC payback period short enough that growth doesn't starve cash flow
• Blended revenue attributable to marketing-led channels, tracked and defended, not assumed
• A steady pace of new channel or approach tests per quarter, with a clear kill or scale decision made on each one, not experiments left to run forever without a verdict

If these terms are unfamiliar to you or you have never been held to them, this is probably not the right role yet. If you already think in these terms by habit, this role gives you the platform to prove it at a larger scale.

What You'll Own

• Awareness and reach across channels: Grow how many of the right people know about us, across paid, organic, and content channels, without confusing reach for revenue
• Revenue and ROI: Own the return on every rupee spent across channels. You inherit working tracking systems (CleverTap, AppsFlyer, Mixpanel); your job is to use them to make better spend decisions, not to build or maintain them
• Segmentation strategy: Build and keep refining how we segment customers by occasion type, guest count, budget band, and lead time to event. Turn that into distinct messaging and targeting for each segment, not one-size-fits-all campaigns
• Growth and channel scaling: Identify, test, and scale marketing channels and approaches beyond what we currently run, with a clear view of what each one returns
• Team direction: Directly lead our content and performance marketing team. You set the direction and the bar. They execute against it. You are not doing their job for them, and you are not letting them run without direction either
• Reporting: Give the founders and CMO clear, ROI-level visibility. What is working, what isn't, what you are cutting, and what you are doubling down on, and why

Required Skills & Background

• A proven, quantifiable track record of improving marketing ROI at a previous company, across more than one channel, not just optimizing a single ad account. Able to state clearly what the return was before, what it became, and what they specifically did to move it.
• 5 to 8 years in marketing, with real time spent owning revenue and channel-level ROI, not just campaign execution
• Experience running and defending a multi-channel budget: knowing when to shift spend between awareness and performance channels based on what the numbers say
• Strong quantitative fluency. Comfortable reading cohort, retention, and attribution data (from tools like CleverTap, AppsFlyer, and Mixpanel) and turning it into a spend or strategy decision, without needing to build the pipelines themselves
• Demonstrated experience building segmentation-led marketing strategy. Able to show, concretely, how they tailored messaging to distinct customer segments in a past role
• Experience managing a team (content and/or performance). This role leads people, not just plans
• Tier-1 educational background (top B-school, or a top engineering institute with demonstrated growth ownership). Exceptions made for candidates with a clearly exceptional track record
• Consumer internet, D2C, e-commerce, or marketplace background strongly preferred. Extra credit for a business with real customer-segment diversity, not a single-SKU product

Good to Have

• Experience marketing a business where the customer's decision changes a lot by occasion, timing, or budget (events, travel, gifting, weddings)
• Experience balancing brand/awareness spend against direct-response spend, and defending that split with numbers
• Prior experience at an early-stage startup where they built the growth function rather than inheriting one
• Hands-on comfort reviewing ad creative and content briefs, even if they are not writing them personally

What We Offer

• Direct ownership of the marketing function, reporting to the founders and CMO
• Working infrastructure from day one: tracking, attribution, and engagement systems are already built, so you spend your time on strategy and ROI, not setup
• Competitive pay, with ESOP and ownership options so your upside grows with the company's
• A team that already executes well. Your job is to point it in the right direction, not build it from zero
• Real accountability: revenue and ROI, not vanity metrics
• Fast growth and more scope as the company scales

Hiring for Data Scientist / Senior Data Scientist

Exp : 4 - 12 yrs

Edu : BE/B.tech/MCA

Work Location : Pune

Notice Period : Immediate - 15 days

Skills :

4+ years of experience in data engineering, data science, or related domains.

Hands-on experience with SQL, Python, and distributed data systems.

Knowledge of machine learning techniques and statistical analysis.

Experience with cloud data platforms (Azure Data Factory, AWS Glue, GCP BigQuery).

Familiarity with DevOps practices and CI/CD for data pipelines.

Platforms & Operations Experience (Preferred)

- Experience working with Azure, AWS, or Google Cloud data tools.

Operational experience with data orchestration tools (Airflow, ADF, Glue).

Understanding of Kubernetes, Docker, or containerized environments.

Hands-on experience with data warehousing platforms (Snowflake, Redshift, BigQuery).

Experience in monitoring, logging, and alerting operations for data workflows.

Job Summary:

We are looking for a skilled Data Scientist with strong expertise in demand forecasting, predictive analytics, and emerging Generative AI technologies. The ideal candidate should have hands-on experience in machine learning, deep learning, NLP, and LLM-based solutions, along with proficiency in Python, SQL, Power BI, and advanced Excel. This role involves building scalable forecasting models and leveraging AI/GenAI to deliver actionable business insights.

Key Responsibilities:

• Develop and deploy demand forecasting models using machine learning and deep learning techniques.
• Analyze historical data to identify trends, seasonality, and demand patterns.
• Build predictive models to improve supply chain and inventory planning.
• Work with large datasets using Python and SQL for data extraction, transformation, and analysis.
• Design dashboards and reports using Power BI for business stakeholders.
• Utilize advanced Excel techniques (Pivot Tables, Power Query, formulas) for analysis and reporting.
• Build and integrate NLP-based solutions for text data analysis and insights.
• Develop and implement LLM-based applications using Generative AI frameworks.
• Design and deploy RAG (Retrieval-Augmented Generation) pipelines for intelligent data retrieval and response generation.
• Collaborate with cross-functional teams (operations, finance, product) to align forecasting and AI solutions.
• Continuously improve model accuracy and performance through experimentation and optimization.

Required Skills:

• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
• Solid understanding of machine learning & deep learning algorithms.
• Experience in demand forecasting / time-series analysis (ARIMA, Prophet, LSTM, etc.).
• Hands-on experience with NLP techniques and libraries (NLTK, SpaCy, Transformers).
• Experience working with LLMs and Generative AI frameworks (OpenAI, Hugging Face, LangChain, etc.).
• Strong understanding of RAG architectures and vector databases (FAISS, Pinecone, etc.).
• Advanced knowledge of SQL for data manipulation.
• Hands-on experience with Power BI for visualization and reporting.
• Expertise in advanced Excel (Power Query, dashboards, data modeling).
• Strong analytical and problem-solving skills. 

Preferred Qualifications:

• Experience in supply chain, logistics, or e-commerce forecasting.
• Knowledge of cloud platforms (AWS, Azure, or GCP).
• Familiarity with data pipelines and ETL processes.
• Understanding of business metrics and KPIs related to demand planning.

Description

We’re seeking a highly skilled, execution-focused Senior Data Scientist with a minimum of 5 years of experience. This role demands hands-on expertise in building, deploying, and optimizing machine learning models at scale, while working with big data technologies and modern cloud platforms. You will be responsible for driving data-driven solutions from experimentation to production, leveraging advanced tools and frameworks across Python, SQL, Spark, and AWS. The role requires strong technical depth, problem-solving ability, and ownership in delivering business impact through data science.

Responsibilities

• Design, build, and deploy scalable machine learning models into production systems.
• Develop advanced analytics and predictive models using Python, SQL, and popular ML/DL frameworks (Pandas, Scikit-learn, TensorFlow, PyTorch).
• Leverage Databricks, Apache Spark, and Hadoop for large-scale data processing and model training.
• Implement workflows and pipelines using Airflow and AWS EMR for automation and orchestration.
• Collaborate with engineering teams to integrate models into cloud-based applications on AWS.
• Optimize query performance, storage usage, and data pipelines for efficiency.
• Conduct end-to-end experiments, including data preprocessing, feature engineering, model training, validation, and deployment.
• Drive initiatives independently with high ownership and accountability.
• Stay up to date with industry best practices in machine learning, big data, and cloud-native deployments.

Requirements

• Minimum 5 years of experience in Data Science or Applied Machine Learning.
• Strong proficiency in Python, SQL, and ML libraries (Pandas, Scikit-learn, TensorFlow, PyTorch).
• Proven expertise in deploying ML models into production systems.
• Experience with big data platforms (Hadoop, Spark) and distributed data processing.
• Hands-on experience with Databricks, Airflow, and AWS EMR.
• Strong knowledge of AWS cloud services (S3, Lambda, SageMaker, EC2, etc.).
• Solid understanding of query optimization, storage systems, and data pipelines.
• Excellent problem-solving skills, with the ability to design scalable solutions.
• Strong communication and collaboration skills to work in cross-functional teams.

Benefits

• Best-in-class salary: We hire strong talent and compensate accordingly.
• Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
• Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
• High-impact work: Build AI-first systems and products used at scale by global clients.

About Us

Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.

Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.