Data Scientist at Acrivision Technologies Pvt Ltd · Pune · 2 - 10 years · ₹2L - ₹15L / yr (ESOP available) · Profitable · Posted 11 Jul 2023
- Lead the data science, ML, product analytics, and insights functions by translating sparse and decentralized datasets to develop metrics, standardize processes, and lead the path from data to insights.
- Building visualizations, models, pipelines, alerts/insights systems, and recommendations in Python/Java to support business decisions and operational experiences.
- Advising executives on calibration strategy, DEI, and workforce planning.

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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.
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.
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)
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.
Sr Engineer – Artificial Intelligence
Job Summary
As an AI Engineer at Emerson, you will be responsible for analysing complex data sets to
identify trends, develop predictive models, and provide actionable insights. You will work closely
with cross-functional teams to understand business needs and deliver data-driven solutions that
enhance decision-making and drive business growth.
In This Role, Your Responsibilities Will Be:
Analyze large, complex data sets using statistical methods and machine learning
techniques to extract meaningful insights.
Develop and implement predictive models and algorithms to solve business problems
and improve processes.
Create visualizations and dashboards to effectively communicate findings and insights to
stakeholders.
Work with data engineers, product managers, and other team members to understand
business requirements and deliver solutions.
Clean and preprocess data to ensure accuracy and completeness for analysis.
Prepare and present reports on data analysis, model performance, and key metrics to
stakeholders and management.
Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint
Retrospective
Stay updated with the latest industry trends and advancements in data science and
machine learning techniques.
For This Role, You Will Need:
Bachelor’s degree in computer science, Data Science, Statistics, or a related field or a
master's degree or higher is preferred.
Total 5-7 years of industry experience
More than 3 years of experience in a data science or analytics role, with a strong track
record of building and deploying models.
Proficiency in programming languages such as Python or R, and experience with data
manipulation libraries (e.g., pandas, NumPy).
Excellent understanding of Agentic Frameworks like Microsoft Agent Framework.
Experience with NLP, NLG, and Large Language Models Open Source as well as Cloud
based models.
Experience with SQL and NoSQL databases such as MongoDB, Cassandra, Vector
databases
Experience with Dockers, Asynchronous Data Orchestrators, environments etc.
Strong analytical and problem-solving skills, with the ability to work with complex data
sets and extract actionable insights.
Excellent verbal and written communication skills, with the ability to present complex
technical information to non-technical stakeholders.
Preferred Qualifications that Set You Apart:
Prior experience in engineering domain would be nice to have
Prior experience in working with teams in Scaled Agile Framework (SAFe) is nice to
have
Possession of relevant certification/s in data science from reputed universities
specializing in AI.
Familiarity with cloud platforms, Microsoft Azure is preferred
Ability to work in a fast-paced environment and manage multiple projects simultaneously.
Strong analytical and troubleshooting skills, with the ability to resolve issues related to
model performance and infrastructure.
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.
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.

🚀 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
Job Description:
As a Data Science Intern, you will collaborate with our data science and analytics teams to work on meaningful projects involving data analysis, predictive modeling, and statistical modeling. You will have the opportunity to apply your academic knowledge in a practical, fast-paced environment, contribute to key data-driven projects, and gain valuable experience with industry-leading tools and technologies.
Responsibilities:
- Assist in collecting, cleaning, and preprocessing data from various sources.
- Perform exploratory data analysis to identify trends, patterns, and anomalies.
- Develop and implement machine learning models and algorithms.
- Create data visualizations and reports to communicate findings to stakeholders.
- Collaborate with team members on data-driven projects and research.
- Participate in meetings and contribute to discussions on project progress and strategy.
- Work with large datasets to clean, preprocess, and analyze data.
- Build and deploy statistical and machine learning models to generate actionable insights.
- Conduct exploratory data analysis (EDA) to uncover trends, patterns, and correlations.
- Assist in the creation of data visualizations and dashboards for reporting insights.
- Support the development and improvement of data pipelines and algorithms.
- Collaborate with cross-functional teams to understand data needs and translate them into actionable analytics solutions.
- Contribute to the documentation and presentation of results, findings, and recommendations.
- Participate in team meetings, brainstorming sessions, and project discussions.
Duration: 03 Months (with the possibility of extending up to 6 months)
MODE: Work From Home (Online)
Requirements:
- Any Graduate / PassOuts / Freasher can apply.
- Currently pursuing a Bachelor's or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
- Proficiency in programming languages such as Python, R, or SQL.
- Strong foundation in statistics, probability, and data analysis techniques.
Benefits
Internship Certificate
Letter of recommendation
Stipend Performance Based
Part time work from home (2-3 Hrs per day)
5 days a week, Fully Flexible Shift
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.





