data science lead

Codvo.ai

<div><div><div><div><div><b>Company Overview</b></div><div>
At <b>Codvo</b>, software and people transformations go hand-in-hand. We are a global empathy-led technology services company where product innovation and mature software engineering are part of our core DNA. <b>Respect, Fairness, Growth, Agility, and Inclusiveness</b> are the core values we aspire to live by every day.</div><div>
We continue to expand our <b>digital strategy, architecture, AI/ML, GenAI, and product engineering</b> capabilities to deliver outside-the-box thinking and measurable business outcomes for our clients.</div><p></p><div><b>
Role Overview</b></div><div>
We are looking for a <b>Senior / Lead Data Scientist</b> with strong expertise in <b>Machine Learning, Deep Learning, and production-grade ML systems</b>, particularly around <b>time-series data, forecasting, and predictive modeling</b>, along with hands-on experience in <b>Generative AI (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI systems</b>.</div><div>
This role requires someone who can <b>design, build, optimize, and productionize ML and GenAI solutions end-to-end</b>, work closely with data engineering teams, and take ownership of complex AI workflows. Prior experience <b>leading small teams or mentoring junior data scientists</b> is strongly preferred.</div><p></p><div><b>
Key Responsibilities</b></div><div><b>
Core ML &amp; Predictive Analytics</b></div><ul><li>
Design, develop, and deploy <b>production-grade ML and DL models</b> with a focus on <b>time-series data, forecasting, and predictive analytics</b>.</li><li>
Build and optimize <b>end-to-end ML pipelines</b>, from data preprocessing and feature engineering to model training, evaluation, deployment, and monitoring.</li><li>
Apply advanced ML techniques including <b>regression, tree-based models, ensemble methods, deep learning, and optimization algorithms</b>.</li><li>
Perform <b>feature extraction and dimensionality reduction</b> using techniques such as <b>autoencoders</b> for high-dimensional datasets.</li><li>
Track experiments, model performance, and metrics using industry-standard tools and best practices.</li></ul><div><b>
GenAI, LLMs &amp; Agentic AI</b></div><ul><li>
Design and implement <b>LLM-powered applications</b>, including <b>Retrieval-Augmented Generation (RAG)</b> systems for enterprise use cases such as analytics automation, knowledge assistants, and decision-support tools.</li><li>
Build <b>document ingestion, chunking, embedding, and retrieval pipelines</b> for structured and unstructured data using vector databases.</li><li>
Develop <b>Agentic AI workflows</b> that enable multi-step reasoning, tool usage, and autonomous task execution.</li><li>
Integrate LLMs with traditional ML systems to enhance <b>explainability, insights generation, and user interaction</b>.</li><li>
Implement <b>guardrails and evaluation mechanisms</b> to reduce hallucinations and ensure reliable, grounded LLM outputs.</li><li>
Optimize LLM inference for <b>latency, cost, and scalability</b> in cloud and hybrid environments.</li></ul><div><b>
Required Skills &ndash; Technical</b></div><ul><li><b>
7+ years</b> of hands-on experience in <b>Data Science, Machine Learning, or Applied AI</b> roles.</li><li>
Strong foundation in <b>statistical modeling and machine learning</b>, including:<ul><li>
Regression, boosting trees, random forests</li><li><b>
Time-series modeling and forecasting</b></li><li>
Optimization techniques (linear, nonlinear, stochastic)</li></ul></li><li><b>
Deep Learning expertise</b>using frameworks such as:<ul><li>
TensorFlow, Keras, PyTorch</li><li>
Experience with <b>RNN, LSTM, GRU, CNN</b> is a plus</li></ul></li><li>
Experience with <b>NLP and unstructured data processing</b>.</li><li>
Hands-on experience with <b>LLMs and GenAI</b>, including:<ul><li><b>
Retrieval-Augmented Generation (RAG)</b></li><li>
Vector databases (FAISS, Chroma, Pinecone, or similar)</li><li>
Prompt engineering and LLM evaluation</li><li>
Agentic AI frameworks (e.g., LangChain, LangGraph, or similar)</li></ul></li><li>
Strong programming skills in <b>Python</b> (R is a plus); familiarity with <b>sh/bash scripting</b>.</li><li>
Experience working with <b>SQL and NoSQL databases</b>.</li><li>
Experience building and consuming <b>REST APIs and web services</b>.</li><li>
Exposure to <b>Big Data tools</b> (Spark, Hadoop, or similar) is a strong plus.</li><li><b>
Cloud experience</b> (AWS / GCP / Azure); exposure to GenAI platforms (AWS Bedrock, Azure OpenAI, Vertex AI) is a plus.</li></ul></div></div></div></div><p></p>

Data Science Lead (India)

Citi

<div><p>The Specialized Analytics Ld Analyst is a strategic professional who stays abreast of developments within own field and contributes to directional strategy by considering their application in own job and the business. Recognized technical authority for an area within the business. Requires basic commercial awareness. There are typically multiple people within the business that provide the same level of subject matter expertise. Developed communication and diplomacy skills are required in order to guide, influence and convince others, in particular colleagues in other areas and occasional external customers. Significant impact on the area through complex deliverables. Provides advice and counsel related to the technology or operations of the business. Work impacts an entire area, which eventually affects the overall performance and effectiveness of the sub-function/job family.<br>
<br>
<b>Responsibilities:</b></p><ul><li>
Incumbents work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of business strategies</li><li>
Identifies and compiles data sets using a variety of tools (e.g. SQL, Access) to help predict, improve, and measure the success of key business to business outcomes</li><li>
Responsible for documenting data requirements, data collection / processing / cleaning, and exploratory data analysis; which may include utilizing statistical models / algorithms and data visualization techniques</li><li>
Incumbents in this role may often be referred to as Data Scientists</li><li>
Specialization in marketing, risk, digital and AML fields possible</li><li>
Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency.</li></ul><p><b><br>
Qualifications:</b></p><ul><li>
10 plus years of experience</li><li>
Working experience in a quantitative field, Financial/Credit Card industry</li><li>
Must have Demonstrated ability in data retrieving and manipulation as well as proficient analytical skills</li><li>
Excellent analytic ability and problem solving skills</li><li>
Proficient in Microsoft Office including excellent MS Excel skills to develop analytic presentations</li><li>
Excellent communication and interpersonal skills, be organized, detail oriented, and adaptive to matrix work environment</li></ul><p><b><br>
Education:</b></p><ul><li>
Bachelors/University degree, Master&rsquo;s degree preferred</li></ul><p></p><p><br>
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.</p><p></p><p>
-</p><p><b>
Job Family Group:
</b></p>Decision Management<p>
-</p><p><b>
Job Family:</b></p>
Specialized Analytics (Data Science/Computational Statistics)<p>
-</p><p><b>
Time Type:</b></p>
Full time<p>
-</p><p><b>
Most Relevant Skills
</b></p>Please see the requirements listed above.<p>
-</p><p><b>
Other Relevant Skills
</b></p>For complementary skills, please see above and/or contact the recruiter.<p>
-</p><p><i>
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.</i></p><p></p><p><i><br>
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review </i><i>Accessibility at Citi</i><i>.</i><br>
<br>
<i>View Citi&rsquo;s </i><i>EEO Policy Statement</i><i> and the </i><i>Know Your Rights</i><i> poster.</i></p></div>

Data Science Lead Analyst - Vice President

Extreme Networks

<div><div>Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. With double-digit growth year over year, no provider is better positioned to deliver scalable outcomes than Extreme.</div><div></div><div><br>
Inclusion is one of our core values and in our DNA. We are committed to fostering an inclusive workplace that embraces our differences and creates an atmosphere where all our employees thrive because of their differences, not in spite of them.</div><div></div><div><br>
Become part of Something big with Extreme! As a global networking leader, learn why there&rsquo;s no better time to join the Extreme team.</div><div></div><div><b><br>
Data Science Engineer, Lead Analyst, Enterprise Data &amp; Analytics
</b></div><div>
</div><div>The Data Science Engineer, Lead Analyst, Enterprise Data &amp; Analytics will be a member of the &ldquo;Expand&rdquo; (Extreme Process Analytics and Data Governance) team, within the Data &amp; Analytics pillar, and is responsible for developing and operationalizing AI/ML models that power predictive insights and automated narratives.
</div><div>This position is remote, reporting to the Director, Data and Analytics, and supports business stakeholders across all functions but be primarily aligned to Sales, Sales Ops, Marketing, and Finance.
</div><div>
</div><div><b>Specific Duties:<br>
</b></div><div></div><br>
<div><b>Domain Experience
</b></div><ul><li> Develop AI/ML models to generate both (1) predictive insights across a range of business functions, including, but not limited to, sales funnel forecasts, inventory drawdowns, back-end rebates, commissions, opportunity scoring, and &ldquo;sales in&rdquo; revenue, and (2) insight narratives to support executive summaries.
</li><li> Build and optimize AI-driven capabilities for &ldquo;Ask EDNA,&rdquo; supporting a search-like capability for metrics, dashboards, ad-hoc generation of metrics, and natural-language responses to business questions.
</li><li> Design and develop visualizations that present forecasted results and correlations.
</li><li> Build statistical correlation models leveraging 3rd party data to provide insight into sales and revenue trends benchmarked against external factors, e.g. market trends, tariffs, etc.
</li><li> Collaborate with cross-functional teams (Sales Operations, Finance, Marketing, Analytics) to understand forecasting and analytics requirements and rapidly translate them into production‑ready AI solutions.
</li><li> Design, implement, and maintain scalable data pipelines and feature engineering workflows using Snowflake and dbt.
</li><li> Ensure data quality, feature robustness, and model reliability through structured experimentation, model validation, and performance monitoring.
</li><li> Partner with peer members of the Analytics team in support of developing the end-to-end analytics solution using a modern technical stack, e.g. Snowflake, DBT, Fivetran, Informatica, Sigma.
</li></ul><div>
</div><div><b>Leadership Planning
</b></div><div>
</div><ul><li> Assist in roadmap and planning activities to scope the level of effort for near- and long-term projects.
</li><li> Provide technical leadership in data science architecture and modeling best practices, AI enablement, and AI security and governance considerations.
</li><li> Independently manage personal backlog of work based on team&rsquo;s priority, with escalation of interdependencies, collaboration opportunities, and potential blockers.
</li><li> Provide updates on progress, risks and mitigation strategies, milestones, and outcomes through the various agile meetings, including stand-ups, planning, refinement, and stakeholder readouts.<br>
</li></ul><div></div><br>
<br>
<div><b>Qualifications:
</b></div><div>Highly self-motivated and able to work independently as well as in a team environment.<br>
</div><div></div><br>
<div><b>Experience:</b></div><ul><li> 3+ years of hands‑on experience in advanced analytics, data science, or AI model development.
</li><li> 2+ years of experience with more than 1 database system, such as Redshift, Azure Synapse, BigQuery, Oracle, SQL Server, MySQL, Snowflake.
</li><li> 2+ years of experience with more than 1 analytics/visualization tool, such as PowerBI, Tableau, Looker, Sigma Computing, or other BI reporting layers.
</li></ul><div>
</div><div><b>Hard Skills
</b></div><ul><li> Strong proficiency in building and deploying predictive models (classification, time‑series forecasting, regression, anomaly detection).
</li><li> Deep expertise in Python, SQL, Snowflake, data pipeline development, and designing and maintaining dbt models.
</li><li> Functional experience implementing a variety of data warehousing concepts and methodologies, including snapshotting, incremental data loads, SCDs, and star schemas.
</li><li> Experience is a plus in (1) managing the ingestion and modeling of the following business application data sources: Salesforce, Oracle Suite (EBS, Fusion, HCM), and Jira, and (2) supporting analytical requirements for Sales, Finance, or Marketing teams.
</li></ul><div>
 </div><div><b>Soft Skills
</b></div><ul><li> Can be highly flexible in adapting to the needs of the team and organization.
</li><li> Comfort in working within an agile team, leveraging DevOps concepts and agile-enablement tools including Jira, Confluence, and Github.
</li><li> Ability to clearly communicate complex project execution plans and technical ideas to both technical and business stakeholders, with demonstrated written and verbal presentation skills to present compelling recommendations.
</li><li> Comfortable working in a fast‑paced, high‑visibility environment with minimal supervision.
</li></ul><div>Salary based on region, qualifications and experience 110,000 to 125,000 plus bonus</div><div></div><div><br>
</div>
<div>Extreme Networks, Inc. (EXTR) creates effortless networking experiences that enable all of us to advance. We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation. Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions and rely on our top-rated services and support to accelerate their digital transformation efforts and deliver progress like never before. For more information, visit Extreme's website or follow us on Twitter, LinkedIn, and Facebook.</div><div></div><div><i><br>
We encourage people from underrepresented groups to apply. Come Advance with us! In keeping with our values, no employee or applicant will face discrimination/harassment based on: race, color, ancestry, national origin, religion, age, gender, marital domestic partner status, sexual orientation, gender identity, disability status, or veteran status. Above and beyond discrimination/harassment based on &ldquo;protected categories,&rdquo; Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (e.g., stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks.</i></div>
<p>
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.</p></div>

Data Science Engineer, Lead Analyst, Enterprise Data & Analytics

Weekday AI (YC W21)

<div>
 <strong>
  This role is for one of the Weekday's clients
  <br/>
  <br/>
 </strong>
 <strong>
  Salary range: Rs 1000000 - Rs 2000000 (ie INR 10-20 LPA)
  <br/>
  <br/>
 </strong>
 Min Experience: 4 years
 <br/>
 <br/>
 Location: Bangalore
 <br/>
 <br/>
 JobType: full-time
 <br/>
 <br/>
 We are looking for a Data Scientist to lead the end-to-end data science lifecycle&mdash;from problem definition and hypothesis development to model deployment planning and performance evaluation. This role focuses on building scalable, production-ready machine learning solutions that drive insights across content, audience, growth, and revenue use cases.
 <br/>
 <br/>
 You will work closely with product, editorial, growth, sales, and engineering teams to identify high-impact opportunities and translate complex data into actionable business outcomes.
 <br/>
 <br/>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <strong>
  <strong>
   Key Responsibilities
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   Own the complete data science workflow including problem framing, feature engineering, model development, validation, and deployment planning
  </li>
  <li>
   Develop and operationalize machine learning models for forecasting, personalization, churn prediction, attribution, ranking, and content intelligence
  </li>
  <li>
   Build content and audience intelligence using NLP techniques such as embeddings, semantic similarity, topic and entity modeling, summarization, and relevance scoring
  </li>
  <li>
   Design sales and advertising analytics solutions including demand forecasting, pricing optimization, uplift modeling, and campaign effectiveness measurement
  </li>
  <li>
   Perform advanced statistical analysis including causal inference, A/B testing, experiment design, incrementality, and uplift measurement
  </li>
  <li>
   Partner with data engineering teams to develop scalable data pipelines and model training workflows
  </li>
  <li>
   Define and maintain unified KPIs and measurement frameworks to evaluate content performance and audience behavior across platforms
  </li>
  <li>
   Monitor model performance, detect drift, ensure robustness, fairness, and governance of deployed models
  </li>
  <li>
   Deliver executive-ready insights through dashboards, automated reports, and clear data storytelling
  </li>
  <li>
   Collaborate with cross-functional teams to prioritize initiatives with the highest business impact
  </li>
  <li>
   Contribute to code and design reviews, mentor peers, and raise analytical standards across the organization
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Required Skills &amp; Experience
  <br/>
  <br/>
 </strong>
 <strong>
  <strong>
   Must-Have
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   4-7 years of applied data science experience delivering measurable business impact
  </li>
  <li>
   Strong proficiency in Python (pandas, NumPy, scikit-learn, statsmodels) and SQL
  </li>
  <li>
   Hands-on experience building and validating ML models including regression, classification, forecasting, clustering, recommendation systems, uplift models, and NLP-based solutions
  </li>
  <li>
   Solid foundation in statistics, probability, hypothesis testing, experimental design, and causal inference
  </li>
  <li>
   Experience working with large-scale datasets and cloud platforms such as AWS, Azure, or GCP
  </li>
  <li>
   Familiarity with BI and visualization tools like Tableau, Power BI, or Plotly
  </li>
  <li>
   Strong analytical thinking, communication, and data storytelling skills
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Good-to-Have
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   Experience with deep learning frameworks such as TensorFlow or PyTorch
  </li>
  <li>
   Exposure to big data technologies like Spark, Hadoop, or Databricks
  </li>
  <li>
   Familiarity with MLOps practices, model monitoring, and production ML workflows
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  <strong>
   Education
   <br/>
   <br/>
  </strong>
 </strong>
 <ul>
  <li>
   Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Key Skills
  <br/>
  <br/>
 </strong>
 Data Science
 <br/>
 <br/>
 <ul>
  <li>
   Python
  </li>
  <li>
   Pandas
  </li>
  <li>
   NLP
  </li>
  <li>
   Machine Learning
  </li>
  <li>
   SQL
  </li>
  <li>
   AWS
  </li>
  <li>
   Statistics
  </li>
  <li>
   Experimentation
  </li>
 </ul>
</div>


Data Scientist

MiQ Digital

<div><p>Role: Principal Data Scientist</p>
<p>
Location: Bengaluru</p>
<p><b>
What you&rsquo;ll do</b></p>
<p>
We&rsquo;re MiQ, a global programmatic media partner for marketers and agencies. Our people are at the heart of everything we do, so you will be too. No matter the role or the location, we&rsquo;re all united in the vision to lead the programmatic industry and make it better.</p>
<p>
As a Principal Data Scientist in our data science department, you&rsquo;ll have the chance to:</p>
<ul>
<li>Provide technical leadership and strategic direction for the data science practice across multiple product teams.</li>
<li>Focus on creating new business opportunities leveraging innovative data science technologies and approaches to solve complex business problems</li>
<li>Drive end-user usage and consumption of Data Science solutions while also striving for technical excellence.</li>
<li>Mentor and guide senior data scientists and engineers, fostering technical growth and excellence within the team.</li>
<li>Driving best practices across teams for - code development, code versioning, unit tests, testing strategies, pipeline architecture, model development &amp; deployment, use of cloud applications, use of AI/ML platforms.</li>
<li>Lead the evaluation and implementation of new data science models, platforms, and technologies to enhance the organization's capabilities.</li>
</ul>
<p><b>Who are your stakeholders?</b></p>
<p>
Internal Consumer/Stakeholders:</p>
<ul>
<li>End Users (Account Managers / Traders / Sales / Analysts): Gather insights into business challenges and user feedback to propose solutions and features for enhanced user experience.</li>
<li>Development Team: Collaborate with Technology Managers to foster technical excellence in product development, ensuring the creation of robust, proven, scalable, data science-driven, and high-impact solutions.</li>
</ul>
<p><b>What you&rsquo;ll bring
</b></p><ul><li>Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.</li>
<li>10 years of hands-on work experience in data science modelling to solve product or business problems.</li>
<li>Experience translating product and business questions into clearly framed investigative projects, performing statistical analysis, and coding (e.g., Python, R, SQL)</li>
<li>Ability to present to business leaders and communicate effectively with highly technical leadership teams.</li>
<li>Understanding of AI Models, Large Language Models, and AI specialized infrastructure especially as it relates to AI trends and enablers within businesses.</li>
<li>Candidates with the ability to set-up and ensure continuous improvement of MLOps &amp; CI/CD processes will be preferred.</li>
<li>Experience in the advertising or ad-tech industry will be a plus.</li>
</ul>
<p>We&rsquo;ve highlighted some key skills, experience and requirements for this role. But please don&rsquo;t worry if you don&rsquo;t meet every single one. Our talent team strives to find the best people. They might see something in your background that&rsquo;s a fit for this role or another opportunity at MiQ.
</p><p>If you have a passion for the role, please still apply.
</p><p><b>What impact will you create?</b></p>
<ul>
<li>Lead the technical strategy and execution of data science initiatives that deliver significant impact across interdependent product lines.</li>
<li>Elevate the technical capabilities of the data science team by driving the adoption of advanced methodologies and best practices.</li>
<li>Ensure the rigor, quality, and ethical integrity of data science outputs across all product domains</li>
<li>Accelerate the experimentation of data science applications by developing rapid POC/MVP to drive business impact.</li>
</ul>
<p><b>What&rsquo;s in it for you?</b></p>
<p>
Our Center of Excellence is the very heart of MiQ, and it&rsquo;s where the magic happens. It means everything you do and everything you create will have a huge impact on our entire global business.</p>
<p>
MiQ is incredibly proud to foster a welcoming culture. We do everything possible to make sure everyone feels valued for what they bring. With global teams committed to diversity, equity, and inclusion, we&rsquo;re always moving towards becoming an even better place to work.</p>
<p><b>
Values</b></p>
<p>
Our values are so much more than statements<b>. </b>They unite MiQers in every corner of the world. They shape the way we work and the decisions we make. And they inspire us to stay true to ourselves and to aim for better. Our values are there to be embraced by everyone so that we naturally live and breathe them. Just like inclusivity, our values flow through everything we do - no matter how big or small.</p>
<ul>
<li><b>We do what we love </b>- Passion</li>
<li><b>We figure it out </b>- Determination</li>
<li><b>We anticipate the unexpected </b>- Agility</li>
<li><b>We always unite </b>- Unite</li>
<li><b>We dare to be unconventional </b>- Courage</li>
</ul>
<p><b>Benefits
</b></p><p>Every region and office has specific perks and benefits, but every person joining MiQ can expect:</p>
<ul>
<li>A hybrid work environment
</li><li>New hire orientation with job-specific onboarding and training</li>
<li>Internal and global mobility opportunities</li>
<li>Competitive healthcare benefits</li>
<li>Bonus and performance incentives</li>
<li>Generous annual PTO paid parental leave, with two additional paid days to acknowledge holidays, cultural events, or inclusion initiatives.</li>
<li>Employee resource groups are designed to connect people across all MiQ regions, drive action, and support our communities.</li>
</ul>
<p><i>Apply today!</i></p>
<p><i>
Equal Opportunity Employer</i></p></div>

Principal Data Scientist

Osol

<div>
 <p>
  <strong>
   Company Overview
  </strong>
 </p>
 <p>
  Osol Tech Pvt. Ltd. is a fast-growing software development and professional services company, pioneering AI/ML-driven innovation across industries. We empower organizations in manufacturing, healthcare, retail, and e-commerce to make smarter, data-driven decisions through advanced analytics, predictive modeling, and AI solutions. Our culture fosters continuous learning, collaboration, and innovation at scale.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Job Summary
  </strong>
 </p>
 <p>
  We are seeking a Senior Data Scientist to lead the design and implementation of advanced analytics and data science solutions. This role requires a strong foundation in statistics, machine learning, data engineering, and domain-driven problem solving.
 </p>
 <p>
  <br/>
 </p>
 <p>
  The ideal candidate will have experience building end-to-end data science solutions &mdash; from exploratory data analysis and feature engineering to production-ready models and business insights. You will collaborate closely with engineers, analysts, and business stakeholders to drive measurable outcomes.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Key Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   Design, build, and evaluate predictive and prescriptive models (regression, classification, forecasting, clustering, recommendation systems).
  </li>
  <li>
   Apply advanced ML methods (gradient boosting, ensemble models, transformers for tabular/text, probabilistic models).
  </li>
  <li>
   Conduct A/B tests and causal inference to measure business impact.
  </li>
  <li>
   Perform exploratory data analysis (EDA) using statistical and visualization tools.
  </li>
  <li>
   Translate data findings into actionable insights with clear storytelling for non-technical audiences.
  </li>
  <li>
   Build dashboards and reports to support decision-making.
  </li>
  <li>
   Work with SQL, Spark, Dask, or BigQuery to process and transform large datasets.
  </li>
  <li>
   Collaborate with data engineers to ensure high-quality, reliable data pipelines.
  </li>
  <li>
   Apply feature engineering, data augmentation, and missing data handling strategies.
  </li>
  <li>
   Contribute to model deployment using MLflow, SageMaker, Vertex AI, or Azure ML.
  </li>
  <li>
   Support model monitoring and retraining strategies.
  </li>
  <li>
   Use Python (Pandas, NumPy, Scikit-learn, Statsmodels, PyTorch/TensorFlow), R, SQL, and Jupyter for analysis and modeling.
  </li>
  <li>
   Use visualization &amp; BI tools (Matplotlib, Seaborn, Plotly, Power BI, Tableau, Looker).
  </li>
  <li>
   Track experiments with MLflow, DVC, or Weights &amp; Biases.
  </li>
  <li>
   Partner with product managers and business teams to frame problems and define success metrics.
  </li>
  <li>
   Mentor junior data scientists and analysts.
  </li>
  <li>
   Champion data-driven decision-making across the organization.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Required Qualifications &amp; Skills
  </strong>
 </p>
 <ul>
  <li>
   Strong programming skills in Python and SQL; familiarity with R or Julia is a plus.
  </li>
  <li>
   Solid foundation in statistics, probability, linear algebra, and hypothesis testing.
  </li>
  <li>
   Experience with machine learning techniques (supervised/unsupervised learning, ensembles, time series).
  </li>
  <li>
   Proficiency with data visualization and ability to communicate insights effectively.
  </li>
  <li>
   Hands-on experience with big data tools (Spark, Dask, BigQuery).
  </li>
  <li>
   Cloud experience with AWS, GCP, or Azure for data science workflows.
  </li>
  <li>
   Familiarity with version control (Git), experiment tracking, and reproducible workflows.
  </li>
  <li>
   Excellent communication, collaboration, and problem-solving skills.
  </li>
  <li>
   Proven ability to mentor junior engineers and lead initiatives.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Preferred Qualifications
  </strong>
 </p>
 <ul>
  <li>
   Domain expertise in manufacturing, healthcare, retail, or e-commerce applications.
  </li>
  <li>
   Experience with NLP or computer vision applied to data-rich use cases.
  </li>
  <li>
   Hands-on experience with causal inference, Bayesian methods, or reinforcement learning for experimentation.
  </li>
  <li>
   Prior open-source contributions, publications, or patents.
  </li>
  <li>
   Experience with BI/analytics strategy and executive-level presentations.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Education &amp; Experience
  </strong>
 </p>
 <p>
  &bull; Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
 </p>
 <p>
  &bull; PhD or strong research experience is a plus, but not required.
 </p>
 <p>
  &bull; 5&ndash;7+ years of professional experience in data science or advanced analytics, with evidence of driving business impact.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   What We Offer
  </strong>
 </p>
 <ul>
  <li>
   High-impact data science projects that solve real-world problems.
  </li>
  <li>
   Continuous learning opportunities with cloud credits, courses, and conference sponsorships.
  </li>
  <li>
   Competitive salary, benefits, and performance-based incentives.
  </li>
  <li>
   Flexible hybrid/remote working environment.
  </li>
  <li>
   A culture of collaboration, innovation, and knowledge sharing.
  </li>
 </ul>
 <p>
  <br/>
 </p>
</div>


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